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MATLAB & Simulink: From Modeling to Digital Communication
Gain expertise in MATLAB & Simulink. Explore essential concepts, techniques, and real-world examples. Master modeling and simulation for digital communication systems.
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Embedded Controls Development: From Design to Deployment
Embedded controls development is a critical area in embedded systems engineering, involving the design, programming, and integration of control systems into hardware platforms. These systems are typically found in devices that perform dedicated functions, ranging from consumer electronics to industrial automation and automotive applications. The development process requires a combination of hardware knowledge, software engineering, and systems integration skills.
What Are Embedded Controls?
Embedded controls are computer-based systems that control specific functions within a larger mechanical or electrical system. They use microcontrollers, digital signal processors (DSPs), or microprocessors to monitor inputs from sensors, process data according to a control algorithm, and output control signals to actuators or other system components. These control loops can be simple (like turning on a fan when a sensor detects high temperature) or complex (like managing engine timing and fuel injection in modern vehicles).
Development Lifecycle
The development lifecycle for embedded controls typically follows several key stages:
Requirements Definition: Understanding what the control system needs to do. This includes identifying input/output interfaces, environmental constraints, performance requirements, and safety or compliance standards.
System Design: Creating a high-level architecture that defines how software and hardware will interact. This stage also involves choosing the right microcontroller or processor, selecting sensors and actuators, and outlining communication protocols.
Software Development: Writing code for the embedded control system, often in C or C++. Developers must consider memory limitations, real-time constraints, and hardware-specific details. This stage includes implementing control algorithms, handling interrupts, and developing communication interfaces such as I2C, SPI, UART, or CAN.
Hardware Integration: Integrating the embedded software with physical components. This includes setting up the development board, connecting sensors and actuators, and testing signal integrity and power consumption.
Testing and Validation: Rigorously testing the control system to ensure it functions as expected under various conditions. Unit testing, integration testing, and hardware-in-the-loop (HIL) simulations are commonly used to verify performance and reliability.
Deployment and Maintenance: After development and testing, the system is deployed into the final product. Ongoing maintenance may involve firmware updates, bug fixes, or performance improvements.
Tools and Platforms
A wide range of tools are used in embedded controls development, including:
Integrated Development Environments (IDEs): Tools like Keil µVision, MPLAB X, STM32CubeIDE, and Arduino IDE are popular for writing and debugging code.
Real-Time Operating Systems (RTOS): Systems such as FreeRTOS or VxWorks provide scheduling, task management, and synchronization capabilities for time-sensitive applications.
Version Control Systems: Git is widely used to manage code versions and support collaborative development.
Simulation and Modeling Tools: MATLAB/Simulink is frequently used in control systems design for simulation and code generation.
In-Circuit Debuggers/Programmers: Tools like JTAG or SWD interfaces allow developers to program and debug the target microcontroller directly.
Challenges in Embedded Controls Development
Developing embedded control systems presents several challenges:
Resource Constraints: Embedded systems often have limited CPU power, memory, and energy availability. Efficient coding and hardware optimization are essential.
Real-Time Requirements: Many control systems must respond within strict timing constraints. Missed deadlines can result in system failure or unsafe behavior.
Hardware Dependence: Embedded software is closely tied to specific hardware, requiring deep knowledge of the processor, peripherals, and electrical characteristics.
Debugging Complexity: Diagnosing problems in embedded systems can be difficult due to limited visibility into internal states and limited logging capabilities.
Safety and Reliability: In industries like automotive or medical devices, the control systems must meet rigorous safety standards such as ISO 26262 or IEC 62304.
Applications
Embedded controls are used in countless applications:
Automotive Systems: Engine control units (ECUs), anti-lock braking systems (ABS), adaptive cruise control, and infotainment systems.
Consumer Electronics: Smart thermostats, washing machines, and robotic vacuum cleaners all rely on embedded control systems.
Industrial Automation: PLCs and industrial controllers manage processes on factory floors, often integrating with SCADA systems.
Aerospace and Defense: Flight control systems, unmanned aerial vehicles (UAVs), and radar systems.
Medical Devices: Infusion pumps, pacemakers, and diagnostic equipment all include embedded control systems to ensure safe and accurate operation.
Trends and Future Directions
The field of embedded controls is rapidly evolving. Several key trends are shaping the future:
IoT Integration: Many embedded systems are now connected to the internet, allowing for remote monitoring, control, and firmware updates.
Edge Computing: More processing is being done on the device itself, reducing the need to send data to the cloud and improving response times.
AI and Machine Learning: Embedded systems are beginning to incorporate ML algorithms for pattern recognition, predictive maintenance, and adaptive control.
Model-Based Design: Tools like Simulink allow engineers to design control systems graphically and automatically generate embedded code.
Cybersecurity: As systems become more connected, securing embedded control systems against hacking and data breaches is becoming essential.
Conclusion
Embedded controls development by Servotechinc is a complex but vital discipline that sits at the heart of modern technology. From managing vehicle dynamics to enabling smart home features, embedded control systems play a crucial role in ensuring that machines operate efficiently, safely, and intelligently. As technology advances, the demand for skilled engineers in this domain will only continue to grow.
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Price: [price_with_discount] (as of [price_update_date] - Details) [ad_1] the availability of the rtl-sdr device for less than $20 brings software defined radio (SDR) to the home and work desktops of EE students, professional engineers and the maker community. The rtl-sdr can be used to acquire and Sample RF (radio frequency) signals transmitted in the frequency range 25Mhz to 1.75Ghz, and the MATLAB and Simulink environment can be used to develop receivers using first principles DSP (digital signal processing) algorithms. Signals that the rtl-sdr hardware can receive include: FM radio, uhf band signals, ISM signals, GSM, 3G and LTE mobile radio, GPS and satellite signals, and any that the reader can (legally) transmit of course! In this book we introduce readers to SDR methods by reviewing and analysing downconverted RF signals in the time and frequency domains, and then provide extensive DSP enabled SDR design exercises which the reader can learn from. The hands-on SDR design examples begin with simple am and FM receivers, and move on to the more challenging aspects of Phy layer DSP, where receive filter chains, real-time channelisers, and Advanced concepts such as carrier synchronisers, digital PLL designs and QPSK timing and Phase synchronisers are implemented. In the book we will also show how the rtl-sdr can be used with SDR transmitters to develop complete communication systems, capable of transmitting payloads such as simple text strings, images and audio across the lab desktop. . Publisher : Zaccheus Entertainment (1 January 2015) Language : English Paperback : 670 pages ISBN-10 : 0992978718 ISBN-13 : 978-0992978716 Item Weight : 1 kg 50 g Dimensions : 21.59 x 3.43 x 27.94 cm Country of Origin : United Kingdom [ad_2]
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Top AI Tools for Engineering Students: A Comprehensive Guide
Artificial Intelligence (AI) is revolutionizing the world, and engineering students are at the forefront of this transformation. From simplifying complex calculations to enhancing productivity, AI tools have become indispensable in the educational journey of engineering students. This comprehensive guide will explore the best AI tools for engineering students and best AI tools for graduate students, providing insights into how these tools can enhance learning, foster creativity, and streamline research processes.
MATLAB: The Powerhouse for Computational Engineering
MATLAB is one of the most widely used tools among engineering students, particularly those specializing in fields like electrical, mechanical, and aerospace engineering. MATLAB’s powerful computational capabilities enable students to solve complex mathematical problems, perform simulations, and analyze data efficiently.
Why MATLAB is a Must-Have AI Tool
Advanced Mathematical Functions: MATLAB offers a wide range of built-in functions for advanced mathematical operations, making it easier for students to handle calculus, algebra, and statistical problems.
Simulink Integration: Simulink, a companion tool to MATLAB, allows for model-based design, which is crucial for control systems, signal processing, and digital communication.
Machine Learning Capabilities: With its robust machine learning toolbox, MATLAB enables students to create predictive models, perform classification tasks, and conduct deep learning experiments.
TensorFlow: A Deep Learning Framework for All Levels
TensorFlow, an open-source deep learning framework developed by Google, is among the best AI tools for engineering students and graduate students alike. It offers extensive libraries for building and training machine learning models, making it ideal for students interested in AI, machine learning, and data science.
Key Features of TensorFlow for Engineering Students
Versatility and Flexibility: TensorFlow supports various platforms, including mobile and embedded devices, making it a versatile choice for students working on diverse projects.
Comprehensive Documentation and Tutorials: TensorFlow provides extensive documentation and tutorials that guide beginners and advanced users alike, making it accessible for students at all levels.
Wide Range of Applications: From natural language processing to computer vision, TensorFlow supports a broad spectrum of applications, enabling students to explore different aspects of AI.
AutoCAD: Revolutionizing Design and Drafting
AutoCAD is a staple in the toolkit of engineering students, especially those focusing on civil, mechanical, and architectural engineering. This software automates the process of creating 2D and 3D designs, making it easier for students to visualize their projects and ideas.
Why AutoCAD Stands Out
Precision and Accuracy: AutoCAD offers high precision in creating detailed designs, which is crucial for engineering students working on complex projects.
Customizability: Students can customize the software with different plugins and tools to suit their specific needs, enhancing productivity and learning efficiency.
AI-Driven Features: With AI integration, AutoCAD now offers features like predictive text and automated dimensioning, making the design process faster and more efficient.
SolidWorks: A 3D CAD Software for Innovative Engineers
SolidWorks is another essential tool for engineering students, particularly those involved in mechanical engineering. It is known for its robust features that facilitate 3D modeling, simulation, and product design.
Benefits of Using SolidWorks
User-Friendly Interface: SolidWorks is known for its intuitive interface, making it easier for students to learn and use the software efficiently.
Powerful Simulation Tools: The software offers advanced simulation capabilities, allowing students to test their designs under various conditions and optimize them accordingly.
Integration with AI and Machine Learning: SolidWorks integrates AI and machine learning algorithms to enhance design processes, predict outcomes, and automate repetitive tasks.
Jupyter Notebooks: An Interactive Environment for Data Science
Jupyter Notebooks is a popular tool among engineering students, especially those focusing on data science and AI. This open-source web application allows students to create and share documents that contain live code, equations, visualizations, and narrative text.
Why Jupyter Notebooks is Essential
Interactive Learning: Jupyter Notebooks supports an interactive environment where students can run code in real-time, visualize data, and document their findings simultaneously.
Supports Multiple Programming Languages: It supports various programming languages such as Python, R, and Julia, making it versatile for students working on different projects.
Integration with AI Libraries: Jupyter Notebooks integrates seamlessly with popular AI libraries such as TensorFlow, PyTorch, and Scikit-Learn, making it easier for students to implement and test machine learning models.
Anaconda: A One-Stop Shop for Data Science and AI
Anaconda is a distribution of Python and R programming languages designed specifically for data science and AI. It is a must-have for engineering students working on machine learning, deep learning, or any data-intensive projects.
Advantages of Anaconda for Engineering Students
Pre-Packaged Libraries: Anaconda comes with hundreds of pre-installed libraries and packages, including NumPy, pandas, TensorFlow, and Keras, saving students the hassle of installing them manually.
Environment Management: It offers easy management of environments and dependencies, allowing students to work on multiple projects with different configurations seamlessly.
Robust Community Support: Anaconda has a strong community and a wealth of resources, including tutorials and forums, where students can get help and share knowledge.
PyCharm: The Python IDE for Professional Development
For engineering students focusing on software development, PyCharm is an excellent choice. This integrated development environment (IDE) is specifically designed for Python programming and supports a wide range of AI and machine learning projects.
Key Features of PyCharm
Intelligent Code Editor: PyCharm offers intelligent code completion, real-time error detection, and refactoring capabilities, enhancing coding efficiency and accuracy.
Integration with AI Tools: It integrates with various AI tools and libraries, making it easier for students to develop and deploy machine learning models.
Version Control Systems: PyCharm supports version control systems like Git and Subversion, which are essential for collaborative projects and maintaining code integrity.
LabVIEW: A Visual Programming Language for Engineers
LabVIEW is a visual programming environment primarily used by engineering students in fields such as electrical and mechanical engineering. It is designed to facilitate data acquisition, instrument control, and industrial automation.
Why Engineering Students Should Use LabVIEW
Visual Programming Interface: LabVIEW’s drag-and-drop interface makes it easier for students to design complex systems without extensive coding knowledge.
Real-Time Data Processing: The software allows for real-time data processing and analysis, which is crucial for engineering experiments and research.
Integration with Hardware: LabVIEW integrates seamlessly with various hardware components, making it ideal for students working on robotics, automation, and embedded systems.
PyTorch: An Open-Source Machine Learning Library
PyTorch, developed by Facebook’s AI Research lab, is another powerful machine learning library widely used by engineering and graduate students. It is particularly known for its dynamic computation graph, which allows for more flexibility and ease of use.
Benefits of Using PyTorch
Dynamic Computational Graphs: Unlike other frameworks, PyTorch provides dynamic computation graphs, making it easier to modify and debug models.
Extensive Library Support: PyTorch offers a wide range of libraries for neural networks, computer vision, and natural language processing, enabling students to experiment with different AI models.
Community and Resources: PyTorch has a robust community and plenty of resources, including tutorials, forums, and research papers, making it easier for students to learn and apply AI concepts.
Wolfram Mathematica: A Tool for Advanced Computation
Wolfram Mathematica is a powerful tool used by engineering students for complex computations, data analysis, and visualization. It combines computational power with an intuitive interface, making it ideal for both classroom learning and research projects.
Why Choose Wolfram Mathematica?
Symbolic Computation: Mathematica excels in symbolic computation, allowing students to solve complex equations and perform algebraic manipulations easily.
Data Visualization: The tool offers robust data visualization capabilities, enabling students to create detailed graphs, charts, and 3D models.
Integration with AI and Machine Learning: Mathematica integrates AI and machine learning functionalities, allowing students to perform tasks like image recognition, predictive analysis, and pattern detection.
Conclusion
The best AI tools for engineering students and graduate students are those that offer versatility, ease of use, and robust capabilities to handle complex tasks. From MATLAB and TensorFlow to AutoCAD and SolidWorks, each tool has unique features that cater to different aspects of engineering education and research. By leveraging these tools, students can enhance their learning experience, improve their problem-solving skills, and stay ahead in the ever-evolving field of engineering. Whether you are an undergraduate just starting out or a graduate student diving deep into specialized research, these AI tools are indispensable for your academic and professional growth.
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MATLAB Simulink Training at Embedded Box
At Embedded Box, Our online community is a vital component of the learning experience. Engage in discussions, collaborate with fellow learners, and benefit from the guidance of experienced instructors and industry professionals who actively participate in our virtual forums. These interactive platforms foster a sense of camaraderie and facilitate valuable networking opportunities, enriching your learning journey with diverse perspectives and experiences.
Furthermore, our Online Embedded Training incorporates continuous assessment and feedback mechanisms to ensure your progress is on track. Regular assessments, quizzes, and practical assignments are strategically integrated to reinforce your learning and provide a robust foundation in embedded systems.
In an ever-evolving technological landscape, our commitment to staying current sets us apart. The content of our online training is regularly updated to reflect the latest trends, tools, and technologies in the dynamic field of embedded systems. This dedication ensures that our learners are not only equipped with fundamental knowledge but are also prepared to navigate and innovate within the rapidly advancing industry.
In conclusion, our Online Embedded Training at Embedded Box is not merely a digital classroom; it's a gateway to empowerment in the world of embedded systems. Whether you're a working professional seeking to enhance your skill set or a student eager to explore this dynamic field, our online training offers a flexible, interactive, and comprehensive learning experience. Join us on this virtual journey of education, collaboration, and skill development, and unlock the doors to a future filled with opportunities in the realm of embedded systems.
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Aerospace engineering colleges in Delhi | Amity University Noida campus
Study from one of the top Aerospace Engineering colleges in Delhi.
The design, development, testing, and production of aircraft, spacecraft, and associated systems and equipment fall within the purview of aerospace engineering. The two main and overlapping sections of the field—aeronautical engineering and astronautical engineering—have historically concentrated on issues relating to air and space flight.
The theory, technique, and application of flight within the earth's atmosphere are the main topics of Aeronautical Engineering.
Astronautical Engineering focuses on science and technology of spacecraft and launch vehicles.
What does Aerospace engineers do?
After graduating from one of the top Aerospace Engineering colleges in Delhi our students can incline towards creating cutting-edge technology and integrate them into aerospace vehicle systems used for transportation, communications, exploration, and defence.
This includes the development and production of missiles, propulsion systems, satellites, and aircraft, as well as the design and testing of aerospace and aviation-related goods, parts, and subassemblies.
Propulsion, materials and constructions, vehicle dynamics and control, software, and aerodynamics are all areas in which successful aerospace engineers excel. It is imperative to study from the best university that prepares you for success.
Mission
Amity Institute of Aerospace Engineering (AIAE) was founded in 2007 under the aegis of Amity University Uttar Pradesh with the goal of fostering Indian traditions and ethos while offering top-notch education. The Institute was founded with the primary goal of advancing comprehensive undergraduate education and doing research in new fields of aerospace engineering that will benefit the country and the world at large. The proposed courses are thorough and on line with international standards.
Laboratories
1. Equipment available at Aircraft Structures Laboratory are:
Digital Fatigue Machine
Two Hinged Arch Apparatus
Wagner Beam Setup
Stroboscope
Whirling speed of shaft apparatus
Logarithmic decrement measuring equipment
Natural frequency measuring system
2. Aerodynamics Lab, equipped with subsonic wind tunnel and smoke tunnel, provides opportunities to study aerodynamic characteristics & flow patterns on different aerofoil, circular cylinder and aircraft test models.
Lab equipment available are,
Wind tunnels
Smoke tunnel
3 Component force balance
Hot wire anemometer
16 Channels pressure scanner
Reynolds apparatus
3. The MATLAB platform is optimized for solving engineering and scientific problems to analyze and design the systems and products transforming our world. Computer Systems & Simulations lab consists of:
Programming in C, C++
MATLAB simulation using Simulink
MATLAB Programming
4. Students can gain huge knowledge of flow field parameter and structural behaviour of aerodynamic control surfaces through accurate flow visualization and flow field property measurements.
FEM / CFD Lab consists of:
Highly specialized lab with Star CCM+ Software and ANSYS 14 Workbench with Mechanical APDL Software
5. Labs of inter-disciplinary domains, are available for students
Elements of Mechanical Engineering Lab, Engineering Mechanics Lab, Applied Physics Lab, Applied Chemistry Lab etc.
Amity Institute of Technology, Aeronautical and Automobile Engineering lab set up by TATA TECHNOLOGIES
How to apply?
Fill your details correctly and submit application form online
Upload softcopy of class X mark sheet and recent color passport size photograph.
Pay as per your preference via. Credit Card/ Debit Card.
Amity is the largest educational organization in India, with over 100,000 students enrolled throughout a 1000-acre campus with cutting-edge technology. Amity is committed to developing leaders who are not simply able professionals but also decent people with morals
Join one of the top Aerospace Engineering colleges in Delhi.
Additionally, if you are looking for the top Acting University in Delhi NCR, Top B. Com (Hons) Colleges in Delhi NCR, B.A. political science honors colleges in Delhi NCR then make sure to visit us on amity.edu
Source :- https://amityuniversitydelhincr.blogspot.com/2023/02/aerospace-engineering-colleges-in-delhi.html
#aerospace engineering colleges in delhi#Top Acting University in Delhi ncr#Top B.Com(Hons) Colleges in Delhi ncr#ba political science honours colleges in delhi ncr
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Matlab Projects
Mat-lab Project Preface to Mechanical DC motor is principally a simple electric motor that uses both an electric field as well as a glamorous field to produce a necklace that can run a motor. This conversion of energy is employed for the generation of electricity. The design “Modeling of Architecture Controlled DC Motor Using MATLAB Project Report” designs a DC motor that's architecture controlled. Hence then the architecture coil is responsible for the magnitude of the current produced.
The Real-time factory uses in performing real-time analysis, simulation, and testing of control systems and digital signal processing (DSP) systems.
The host-target terrain allows druggies to connect models created in Math Works design like Simulink, Matlab, and Real-Time Factory, to physical systems, and execute in real-time. The control algorithm was also developed in the forward or rear direction.
We are providing you with some of the greatest ideas for building Final Year projects with proper guidance and assistance. Takeoff Projects supports final year projects for computing and Engineering, Computer Networks, Computer Communications, Computer Applications, and knowledge Technology streams that cause BS/ME/MTECH/MS/MSC – any Post Graduate degree courses offered by the schools across India.
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Best List of Matlab Commands With Advanced Examples
Here we are going to reveal to you everything about Matlab orders. Be that as it may, before we begin. How about we have a review of Matlab. Matlab is intended for specialists and PC researchers; that is the reason it tends to be shortened as a Matrix-based programming language. Matlab offers fantastic answers for the different computational numeric estimations. It can use to:
Advancement of calculations.
Information examination.
Manifestations of uses and models.
Matlab saw as an incredible use in the event of inside and out learning and AI as this can manage n-measurement space. These spaces can be utilized to investigate and speak to the information into the network structure. Other than this, there are a few advances that are utilizing this method for picture preparing, control framework plan, and computational account.
What are Matlab commands?
Matlab is utilized for intelligent codes for information representation and numerical calculations. One can utilize various types of orders by composing them in Matlab brief '>>' on the indicated order window.
In this post, you will get the rundown of various Matlab orders that are utilized for various purposes.
Matlab Commands for system working
Matlab offers a few orders that are valuable for framework working, for example, sparing the work inside the workspace as a stacking document or as a record. It offers a few Matlab orders for framework related work, for example, posting documents inside the index, showing dates, showing current bearings, and significantly more. The table that is appeared beneath has some Matlab orders that utilization for framework related work
Example 1
octave: 11> pwd
ans =/home/00
octave: 12> x = 3
x = 3
octave: 13> x = 4
x = 4
octave: 14> who
Factors in the current extension:
ans x
Example 2:
octave: 4> type y
y is variable
4
octave: 5> type x
x is a variable
3
Matlab commands in a session management
There are different Matlab orders that are utilized for dealing with a meeting. The table has offered each one of those orders:
Example 1:
octave: 15> x = 5
x = 5
octave: 16> y = 4
y = 4
octave: 17> who
Factors in the current extension:
ans x y
Example 2:
octave: 1> clear
octave: 2> type x
mistake: type: 'x' unclear
octave: 3> type y
mistake: type: 'y' unclear
Matrix, Vector, and Array Matlab commands
The given table will speak to a few orders that can be utilized for working with framework, vector, and exhibit:
Example1:
octave: 18> array1 = [4,5,6]
octave: 20> cat(4, array1)
ans =
4 5 6
octave: 21> length (array2)
ans = 3
octave: 22> max (cat (4, array1, array2))
ans =
7 8 9
octave: 23> max(array1)
ans = 3
octave: 18> min(array2)
ans = 7
Example 2:
Octave: 19> a = [1 2 3; 4 5 6; 7 8 9]
a =
1 2 3
4 5 6
7 8 9
octave: 20> b = [1 1 1; 0 0 0; 1 2 3]
b =
1 1 1
0 0 0
1 2 3
octave: 21> rank(a)
ans = 2
octave: 22> rank)b)
ans = 2
det(a)
ans = 6.6613e-16
octave: 23> det(b)
ans = 0
octave: 24> inv(a)
Warning: matrix singular to machine precision, rcond = 1.54198e-18
ans =
-4.5036e+15 9.0072e+15 -4.5036e+15
9.0072e+15 -1.8014e+16 9.0072e+15
-4.5036e+15 9.0072e+15 -4.5036e+15
Conclusion
Matlab can be used for high-level codings and scientific calculations that can be utilized for an interactive platform to execute complicated calculations in a more effective manner. Matlab commands use to support modules of different operations that are integrated with Simulink. Besides this, it uses for simulation the control system of electronics that can compute digital signal processing, video processing, numerical methods, image processing, and much more. If you face any problem with your Matlab assignments, then contact us. We are the best Matlab Assignment Help providers who can solve your programming queries within the slotted time. We can deliver high-quality data with zero plagiarism at reasonable prices. So, looking for Matlab help, just communicate with us and get life experiences.
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Why Should We Use Matlab - Common Question of Electrical Students
Engineers who are from the electrical background, they are linked with the idea of complex systems. This includes precise mathematical calculations. This also contains the data analysis with the manual method, which is a fierce one. In this scenario, MATLAB and Simulink Modeling come where the tremendous computational capability takes place to analyze those data.
MATLAB is a programming language that is used for scientific computing. It was created to help digital computation without the use of other programming languages like C or FORTRAN. The use of Matlab and Simulink Modeling is used to solve several problems. For solving Matlab applications, knowledge of coding in Matlab is required. There are various software toolboxes available from Mathworks software. This delivers extra functionality required to solve queries in an extensive area of controls like
Computational biology
Image as well as video processing
Optimization
Partial differential equations
Signal processing as well as communications
Statistics along with the data analysis
Is It Necessary to Learn Matlab for Electrical Students?
At the academic level, it is important to know MATLAB. It is a great software for learning image processing and data analysis. In the organization, it depends on the type of the company and as a MATLAB expert, an employee will work as an engineer. Suppose anybody gets a job includes system-level modeling then MATLAB a Simulink is a powerful software to solve. But several companies are using different tools. As per the automotive sector, MATLAB, as well as Simulink software, are directly into vehicle ECUs. It is the model for a function programmer for special characteristics but not at all safe in a critical situation. Several firms don’t use MATLAB at all.
Learning MATLAB is not at all hard for electrical students, but it is a key skill for them. It is a learning paradigm that transfers between other languages and simulation environments. If any electrical engineer has an opportunity to learn then he or she should do it. Any engineer can learn this tool because it is a universal tool in the industry. Lots of medium levels companies are avoiding MATLAB because it has high license expenses, it is ill-suited for several kinds of electronic deployment.
Initially coding in MATLAB is not so easy for electrical students. Collage and Universities give several assignments on MATLAB. There are several companies are available online that provide MATLAB assignment help and assist their students for better understanding. Those online companies not just delivering MATLAB assignments for electrical engineers even they provide electrical engineering assignment help as well.
Use of MATLAB
MATLAB is a combination tool of calculation, visualization, and programming. The platform is easily usable and is all conveyed in mathematical formulas. This tool is written in C, C++ and JAVA language. This scripting language contains several mathematical concepts. Those are as follows
Variables
Vectors and matrices
Structures
Functions
Function handles
Object-oriented features
Top 15 use of MATLAB are as follows
Embedded Systems
Control systems
Digital signal processing
Wireless communications
Image processing and computer vision
Internet of Things
FPGA Design and Codesign
Mechatronics
Test and Measurement
Computational Biology and Computational finance
Robotics
Data Analytics
Predictive Maintenance
Motor and power control
Deep Learning
MATLAB Applications
MATLAB has lots of applications such as
The Aerospace toolbox is used for evaluating the navigation. It is used to visualize the flight simulator.
The Audio toolbox is used for, speech analysis, audio processing, and acoustic measurement.
Electric vehicle designing is used for forming electric vehicles as well as inspect their act with a switch in system inputs.
Mapping has numerous applications in several domains. In Big data, the MapReduce tool is essential for data handling. It has various applications in the real world.
In the area of Machine Learning, Deep Learning, and Artificial intelligence, MATLAB is used a lot.
Several industries use MATLAB across the world. Those are
Automotive
Biological Sciences
Biotech and Pharmaceutical
Chemicals and Petrochemical
Communications
Electronics
Earth, Ocean, and Atmospheric Sciences
Energy Production
Financial Services
Industrial Automation and Machinery
Medical Devices
Software and internet
Metals, Materials, and Mining
Neuroscience
Railway Systems
Coding in MATLAB
In the beginner’s level, coding in MATLAB is not so easy. If anybody has a basic knowledge of Objective C, then he or she will easily catch that language. Lots of things to learn in MATLAB codings such as syntax, variable, function, loop, condition, case, and many more. Assignment helps companies are guiding their students in a different programming language, MATLAB is one of them. So as per the topic, MATLAB is a very important tool to learn for electrical students and this skill will help them in the upcoming future.
#matlab assignment help#electrical engineering assignment help#coding in matlab#use of matlab#matlab applications
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Robotics Engineer job at Infinium Robotics Singapore
Infinium Robotics is an award-winning Robotics Startup specialising in applying revolutionary aerial and ground robotics in the logistics and entertainment sectors. We recently won the Best Valued Future Idea Startup Award at the DHL Innovation Day 2017 and we are also an award recipient of a $750,000 TECS grant from SPRING Singapore. We have recently closed a pre-Series A round and we are starting to hire talented people to join our team. Join us to create revolutionary robotics solutions that will benefit the world!
We’re looking for an experienced Robotics Engineer who will work with a group of skilled engineers in the development of mobile robotics and drones applications.
Main activities:
· Developing proof-of-concept implementations, prototypes and demos to fine-tune technologies to practical, state-of-the-art systems.
· Work on the improvement of indoor navigation techniques for autonomous drones
· Work in the development of autonomous systems for the market
· Work in HIL simulations development for the virtual testing of systems.
Job Requirements:
· Bachelors or Masters in Computer Science, Electronics or equivalent Engineering degree.
· Familiarity with most common programming tools such as: C, cplusplus, Python, Matlab/Simulink.
· Familiarity with Linux and Windows.
· Knowledge of practical electronics (use of multimeter, oscilloscope, analog and digital signals, sensors, actuators)
· Experience with embedded systems (SBCs for rapid prototyping, microcontrollers, embedded C, comms (SPI, I2C, UART))
· Understanding of and experience with any of the following topics but not limited to: Sensor fusion (complementary, kalman, EKF,..), SLAM for indoor navigation, trajectory generation methods and obstacle avoidance techniques, positioning systems, Software/Hardware in the loop, Simulation (Gazebo, xPlane).
· 2+ years of Robotics engineering or research experience
· Citable projects demonstrating robotics engineering abilities
· Good verbal and written communication skills.
Following additional knowledge will not be required, but considered as a plus:
· Mavlink protocol knowledge
· Encryption protocols
· Embedded Operating Systems (RTOS, Embedded Linux,..)
· Digital electronics (components selection, PCB design, Instrumentation…)
StartUp Jobs Asia - Startup Jobs in Singapore , Malaysia , HongKong ,Thailand from http://www.startupjobs.asia/job/27518-robotics-engineer-others-job-at-infinium-robotics-singapore Startup Jobs Asia https://startupjobsasia.tumblr.com/post/160074820074
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Mastering MATLAB and Simulink: From Modelling to Digital Communication Applications
In the dynamic world of engineering and technology, MATLAB and Simulink have become indispensable tools for professionals involved in modeling, simulation, and digital communication systems. As the demand for advanced analytical capabilities continues to grow, mastering these platforms is essential for anyone looking to excel in this field. This guide will take you through the fundamentals of MATLAB and Simulink, their applications in digital communication, and how TechSource Asia can help you become proficient in these powerful tools.
Introduction to MATLAB and Simulink for Modelling and Simulation
MATLAB and Simulink are two of the most widely used software platforms for modeling and simulation across various engineering disciplines. MATLAB provides a high-level programming environment for numerical computation, visualization, and application development, while Simulink offers a block diagram environment for multi-domain simulation and model-based design.
These platforms are essential for engineers and scientists who need to design, simulate, and analyze complex systems. Whether you are working on control systems, signal processing, or digital communication, MATLAB and Simulink provide the flexibility and power needed to bring your ideas to life.
Understanding Simulink’s Capabilities
Simulink is a versatile tool that enables users to create detailed models of systems and processes. Its drag-and-drop interface allows you to build complex models using pre-built blocks, making it easier to visualize and simulate the behavior of systems in real time. Simulink is particularly useful for simulating dynamic systems, where understanding the temporal evolution of signals and states is crucial.
With Simulink online, you can easily access this powerful tool from anywhere, ensuring that your projects remain on track no matter where you are.
Seamless Integration with MATLAB
One of the key strengths of Simulink is its seamless integration with MATLAB. This integration allows users to leverage MATLAB’s computational capabilities directly within Simulink models. You can write custom scripts in MATLAB, use them to drive simulations in Simulink, and analyze the results—all within a unified environment. This synergy between MATLAB and Simulink enhances your ability to develop, test, and refine models more efficiently.
Advantages of Model-based Design
Model-based design (MBD) is a methodology that uses models as the primary means of design and verification. Simulink’s support for MBD enables engineers to move from concept to deployment faster and with greater accuracy. By simulating and testing models before implementation, you can identify and address potential issues early in the design process, reducing development time and costs.
At TechSource Asia, we provide tools and training that empower you to fully utilize model-based design, ensuring that your projects meet the highest standards of performance and reliability.
Exploring Simulink Features
Simulink offers a wide range of features designed to enhance your modeling and simulation experience. Some of the key features include:
Simulation Manager: Manage and run multiple simulations in parallel, optimizing your workflow and reducing simulation time.
Stateflow: Model and simulate decision logic using state machines and flow charts.
Data Import/Export: Easily import data from external sources and export simulation results for further analysis.
Code Generation: Automatically generate C, C++, and HDL code from your models, facilitating deployment in real-time systems.
These features make Simulink a powerful tool for tackling complex engineering challenges, whether in academia, industry, or research.
Top 5 Applications of MATLAB and Simulink in Digital Communication Systems
MATLAB and Simulink are extensively used in the field of digital communication systems. Here are five top applications where these tools shine:
Signal Processing and Modulation
Signal processing is at the heart of digital communication. MATLAB and Simulink provide tools for designing and simulating modulation schemes, filtering, and signal analysis, ensuring optimal performance of communication systems.
Channel Modeling and Equalization
Accurate channel modeling is crucial for understanding how signals propagate in different environments. Simulink’s simulation capabilities allow for the modeling of various channel conditions, helping engineers design robust equalization techniques to mitigate signal degradation.
Error Correction Coding
Error correction is essential for reliable communication over noisy channels. MATLAB and Simulink support the design and simulation of various error correction codes, such as Reed-Solomon and Turbo codes, which are critical for maintaining data integrity in digital communication systems.
Synchronization and Timing Recovery
Synchronization and timing recovery are vital for ensuring that transmitted signals are correctly received and interpreted. Simulink provides tools for simulating and testing synchronization algorithms, helping engineers fine-tune their systems for optimal performance.
Network Simulation
Simulink enables the simulation of entire communication networks, from the physical layer to the application layer. This capability is particularly valuable for testing and validating the performance of communication protocols and network architectures before deployment.
Master MATLAB and Simulink Through TechSource Asia’s In-person and Online Training Courses
To fully leverage the power of MATLAB and Simulink, it’s essential to have a solid understanding of their capabilities and applications. TechSource Asia offers comprehensive MATLAB training courses designed to help you master these tools, whether you’re a beginner or an experienced user.
Comprehensive Learning Opportunities
Our training courses cover everything from the basics of MATLAB and Simulink to advanced techniques for digital communication systems. We offer both in-person and Simulink online courses to accommodate your learning preferences.
Hands-on Experience with Cutting Edge Tools
TechSource Asia’s training programs emphasize practical, hands-on experience. You’ll work with real-world data and industry-standard tools, gaining the skills you need to apply MATLAB and Simulink to your projects confidently.
Practical Application and Industry Relevance
Our courses are designed with industry relevance in mind, ensuring that the skills you acquire are directly applicable to your work. Whether you’re interested in MATLAB consultancy or exploring digital communication systems, our training will equip you with the knowledge and experience to succeed.
Flexible Learning and Expert Support
With TechSource Asia’s flexible learning options, you can choose the training format that best suits your schedule. Our expert instructors are always available to provide guidance and support, ensuring that you get the most out of your learning experience.
Start Your Journey with MATLAB and Simulink Today
Whether you’re new to MATLAB and Simulink or looking to enhance your skills, TechSource Asia offers everything you need to succeed. From free MATLAB trials to comprehensive training courses, we’re here to support you every step of the way. Explore our MATLAB and Simulink resources today and take the first step towards mastering these powerful tools.
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Robotics Engineer job at Infinium Robotics Singapore
Infinium Robotics is an award-winning Robotics Startup specialising in applying revolutionary aerial and ground robotics in the logistics and entertainment sectors. We recently won the Best Valued Future Idea Startup Award at the DHL Innovation Day 2017 and we are also an award recipient of a $750,000 TECS grant from SPRING Singapore. We have recently closed a pre-Series A round and we are starting to hire talented people to join our team. Join us to create revolutionary robotics solutions that will benefit the world!
We’re looking for an experienced Robotics Engineer who will work with a group of skilled engineers in the development of mobile robotics and drones applications.
Main activities:
· Developing proof-of-concept implementations, prototypes and demos to fine-tune technologies to practical, state-of-the-art systems.
· Work on the improvement of indoor navigation techniques for autonomous drones
· Work in the development of autonomous systems for the market
· Work in HIL simulations development for the virtual testing of systems.
Job Requirements:
· Bachelors or Masters in Computer Science, Electronics or equivalent Engineering degree.
· Familiarity with most common programming tools such as: C, cplusplus, Python, Matlab/Simulink.
· Familiarity with Linux and Windows.
· Knowledge of practical electronics (use of multimeter, oscilloscope, analog and digital signals, sensors, actuators)
· Experience with embedded systems (SBCs for rapid prototyping, microcontrollers, embedded C, comms (SPI, I2C, UART))
· Understanding of and experience with any of the following topics but not limited to: Sensor fusion (complementary, kalman, EKF,..), SLAM for indoor navigation, trajectory generation methods and obstacle avoidance techniques, positioning systems, Software/Hardware in the loop, Simulation (Gazebo, xPlane).
· 2+ years of Robotics engineering or research experience
· Citable projects demonstrating robotics engineering abilities
· Good verbal and written communication skills.
Following additional knowledge will not be required, but considered as a plus:
· Mavlink protocol knowledge
· Encryption protocols
· Embedded Operating Systems (RTOS, Embedded Linux,..)
· Digital electronics (components selection, PCB design, Instrumentation…)
StartUp Jobs Asia - Startup Jobs in Singapore , Malaysia , HongKong ,Thailand from http://www.startupjobs.asia/job/27518-robotics-engineer-others-job-at-infinium-robotics-singapore
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Analog Passband Modulation Methods and Analog Modulation Features | Soukacatv.com
Analog Modulation Features
In most communication medium, only a fixed range of frequencies is available for transmission. One way to communicate a message signal whose frequency spectrum does not fall within that fixed frequency range, or one that is otherwise unsuitable for the channel, is to alter a transmittable signal according to the information in your message signal. This alteration is called modulation, and it is the modulated signal that you transmit. The receiver then recovers the original signal through a process called demodulation. This section describes how to modulate and demodulate analog signals using blocks.
HDMI Encoder Modulator,16in1 Digital Headend, HD RF Modulator at Soukacatv.com
Open the Modulation library by double-clicking its icon in the main Communications Toolbox™ block library. Then, open the Analog Passband sublibrary by double-clicking its icon in the Modulation library.
The following figure shows the modulation techniques that Communications Toolbox supports for analog signals. As the figure suggests, some categories of techniques include named special cases.
For a given modulation technique, two ways to simulate modulation techniques are called baseband and pass band. This product supports pass band simulation for analog modulation.
The modulation and demodulation blocks also let you control such features as the initial phase of the modulated signal and post-demodulation filtering.
Represent Signals for Analog Modulation
Analog modulation blocks in this product process only sample-based scalar signals. The input and output of the analog modulator and demodulator are all real signals.
All analog demodulators in this product produce discrete-time, not continuous-time, output.
Adjacent Channel 16 In 1 Analog Headend For Hotel Cable TV System
24 In 1 Analog Fixed Channel Modulator Headend
Representing Analog Signals Using MATLAB
To modulate an analog signal using MATLAB®, start with a real message signal and a sampling rate Fs in hertz. Represent the signal using a vectorx, the entries of which give the signal's values in time increments of 1/Fs. Alternatively, you can use a matrix to represent a multichannel signal, where each column of the matrix represents one channel.
For example, if t measures time in seconds, then the vector x below is the result of sampling a sine wave 8000 times per second for 0.1 seconds. The vector y represents the modulated signal.
Fs = 8000; % Sampling rate is 8000 samples per second.
Fc = 300; % Carrier frequency in Hz
t = [0:.1*Fs]'/Fs; % Sampling times for .1 second
x = sin(20*pi*t); % Representation of the signal
y = ammod(x,Fc,Fs); % Modulate x to produce y.
figure;
subplot(2,1,1); plot(t,x); % Plot x on top.
subplot(2,1,2); plot(t,y)% Plot y below.
As a multichannel example, the code below defines a two-channel signal in which one channel is a sinusoid with zero initial phases and the second channel is a sinusoid with an initial phase of pi/8.
Fs = 8000;
t = [0:.1*Fs]'/Fs;
x = [sin(20*pi*t), sin(20*pi*t+pi/8)];
Analog Modulation with Additive White Gaussian Noise (AWGN) Using MATLAB
This example illustrates the basic format of the analog modulation and demodulation functions. Although the example uses phase modulation, most elements of this example apply to other analog modulation techniques as well.
The example samples an analog signal and modulates it. Then it simulates an additive white Gaussian noise (AWGN) channel, demodulates the received signal, and plots the original and demodulated signals.
% Prepare to sample a signal for two seconds,
% at a rate of 100 samples per second.
Fs = 100; % Sampling rate
t = [0:2*Fs+1]'/Fs; % Time points for sampling
% Create the signal, a sum of sinusoids.
x = sin(2*pi*t) + sin(4*pi*t);
Fc = 10; % Carrier frequency in modulation
phasedev = pi/2; % Phase deviation for phase modulation
y = pmmod(x,Fc,Fs,phasedev); % Modulate.
y = awgn(y,10,'measured',103); % Add noise.
z = pmdemod(y,Fc,Fs,phasedev); % Demodulate.
% Plot the original and recovered signals.
figure; plot(t,x,'k-',t,z,'g-');
legend('Original signal','Recovered signal');
Other examples using analog modulation functions appear in the reference pages for ammod, amdemod, ssbdemod, and fmmod.
Sampling Issues in Analog Modulation
The proper simulation of analog modulation requires that the Nyquist criterion be satisfied, taking into account the signal bandwidth.
Specifically, the sample rate of the system must be greater than twice the sum of the carrier frequency and the signal bandwidth.
Filter Design Issues
After demodulating, you might want to filter out the carrier signal. The particular filter used, such as butter, cheby1, cheby2, and ellip, can be selected on the mask of the demodulator block. Different filtering methods have different properties, and you might need to test your application with several filters before deciding which is most suitable.
Varying Filter's Cutoff Frequency Using Simulink
In many situations, a suitable cutoff frequency is half the carrier frequency. Because the carrier frequency must be higher than the bandwidth of the message signal, a cutoff frequency chosen in this way properly filters out unwanted frequency components. If the cutoff frequency is too high, the unwanted components may not be filtered out. If the cutoff frequency is too low, it might narrow the bandwidth of the message signal.
The following example modulates a sawtooth message signal, demodulates the resulting signal using a Butterworth filter, and plots the original and recovered signals. The Butterworth filter is implemented within the SSB AM Demodulator Passband block.
To open this model , enter doc_filtercutoffs at the MATLAB command line.
This example generates the following output:
There is invariably a delay between a demodulated signal and the original received signal. Both the filter order and the filter parameters directly affect the length of this delay.
Other Filter Cutoffs. To see the effect of a lowpass filter with a higher cutoff frequency, set the Cutoff frequency of the SSB AM Demodulator Passband block to 49, and run the simulation again. The new result is shown below. The higher cutoff frequency allows the carrier signal to interfere with the demodulated signal.
To see the effect of a lowpass filter with a lower cutoff frequency, set the Cutoff frequency of the SSB AM Demodulator Passband block to 4, and run the simulation again. The new result is shown in the following figure. The lower cutoff frequency narrows the bandwidth of the demodulated signal.
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Useful Tutorial Videos
Python Tutorial Videos for Scientific Computing https://www.youtube.com/playlist?list=PL6izMgVOG4_ODaufUQ0AjBrvm54cDFrSW
Embedded System Video tutorials Link https://www.youtube.com/playlist?list=PLd9J3wW9xxHt16J9x5TmXbemU1yycD8oZ
Matlab & Simulink Video tutorials related link https://www.youtube.com/playlist?list=PL6izMgVOG4_OTQuabc5YPWZBFAhXMC0_V
Image Processing Based Video tutorials Link https://www.youtube.com/playlist?list=PL6izMgVOG4_OM0rYxY_iO7ZqhSRcdG9lD
Analog and Digital Communication Based Video tutorials Link https://www.youtube.com/playlist?list=PL6izMgVOG4_MHNK3erTo4-qJy_wnbRgKe
DSP Tutorial Series using Matlab & Python https://www.youtube.com/playlist?list=PL6izMgVOG4_Mdfe0bxBoo8QZTUeHGPxfq
Speech and Audio Processing https://www.youtube.com/playlist?list=PLd9J3wW9xxHsbPX5s-i4-tcItHvuDIjad
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Communications Principles and Systems Both Manually and Using MATLAB/Simulink
New Post has been published on https://www.essayyard.com/communications-principles-and-systems-both-manually-and-using-matlab-simulink/
Communications Principles and Systems Both Manually and Using MATLAB/Simulink
ULO b: Apply and evaluate the principles used in the generation, transmission and reception of digitally modulated signals. ULO c: Report on the characteristics of sampling and analogue to digital conversion and source coding. ULO f: Apply the techniques of, and report on, digital communication applications using Matlab and hardware devices
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Designing MATLAB GUI for various Analog and Digital Communication Systems
By Mohit Sharma | Subham Sharma | Gaurav Sahu"Designing MATLAB GUI for various Analog and Digital Communication Systems"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017,
URL: http://www.ijtsrd.com/papers/ijtsrd8269.pdf
http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/8269/designing-matlab-gui-for-various-analog-and--digital-communication-systems/mohit-sharma
international peer reviewed journal, call for paper health science, ugc approved engineering journal
MATLAB is widely used technical computing software. MATLAB provides graphical design tools such as Simulink and Dials. This paper deals in designing modulation and demodulation techniques of various analog and digital communication systems like AM, FM, PM, PAM, PWM, PPM, PCM, ASK, FSK, PSK, MSK, QPSK, BPSK, BFSK, DSB-SC, SSB-SC. A graphical user interface provides a familiar environment to work. This environment contains pushbuttons, toggle buttons, lists, menus, text boxes, and so forth, all of which are already familiar to the user, so that he or she can concentrate on using the application rather than on the mechanics involved in doing things. Many MATLAB products, such as Curve Fitting Toolbox, Signal Processing Toolbox and Control System Toolbox include apps with custom user interfaces. However, GUIs are harder for the programmer because a GUI-based program must be prepared for mouse clicks (or possibly keyboard input) for any GUI element at any time. Such inputs are known as events, and a program that responds to events is said to be event driven. A graphical User interface (GUI) is a system of graphical elements that allow a user to interact with software using mouse application. GUI can also display data in tabular form or as plots, and can group related components. The graphical user interface (GUI), is a type of user interface that allows users to interact with electronic devices through graphical icons and visual indicators such as secondary notation, instead of text-based user interfaces, typed command labels or text navigation.
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