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https://www.laserfocusworld.com/test-measurement/article/55253453/the-battle-of-lidar-sensor-technologies-fmcw-vs-tof

FMCW LiDAR technology has the potential to “see” through walls to some extent, primarily by detecting the reflected signals from objects or materials behind a wall, depending on the wall’s composition and thickness. Here are some key points regarding this application:

Material Penetration: FMCW LiDAR can penetrate certain materials better than traditional LiDAR systems, especially if the walls are made of less dense materials like drywall or wood. However, it may struggle with more solid materials like concrete or metal.

Detection of Objects: By analyzing the reflected signals, FMCW LiDAR can help identify the presence of objects behind walls, which could be useful in various applications, such as search and rescue operations, construction, or security assessments.

Imaging Capabilities: Advanced processing techniques can be applied to the data collected by FMCW LiDAR to create images or 

maps of the environment behind walls, although this is still an area of ongoing research and development.

Safety and Efficiency: This capability can enhance safety for first responders in emergency situations, allowing them to assess environments without direct access.

#through-wall imaging

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https://www.pnas.org/doi/abs/10.1073/pnas.2408975122

link sharing for the specific PNAS article ('https://www.pnas.org/doi/abs/10.1073/pnas.2408975122') :

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Researchers use magnetic systems to artificially reproduce the learning and forgetting functions of the brain

With the advent of Big Data, current computational architectures are proving to be insufficient. Difficulties in decreasing transistors’ size, large power consumption and limited operating speeds make neuromorphic computing a promising alternative.

Neuromorphic computing, a new brain-inspired computation paradigm, reproduces the activity of biological synapses by using artificial neural networks. Such devices work as a system of switches, so that the ON position corresponds to the information retention or “learning,” while the OFF position corresponds to the information deletion or “forgetting.”

In a recent publication, scientists from the Universitat Autònoma de Barcelona (UAB), the CNR-SPIN (Italy), the Catalan Institute of Nanoscience and Nanotechnology (ICN2), the Institute of Micro and Nanotechnology (IMN-CNM-CSIC) and the ALBA Synchrotron have explored the emulation of artificial synapses using new advanced material devices. The project was led by Serra Húnter Fellow Enric Menéndez and ICREA researcher Jordi Sort, both at the Department of Physics of the UAB, and is part of Sofia Martins Ph.D. thesis.

Read more.

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Rappert B. A framework for the assessment of non-lethal weapons. Med Confl Surviv. 2004 Jan-Mar;20(1):35-54. doi: 10.1080/13623690412331302284. PMID: 15015546.

https://pubmed.ncbi.nlm.nih.gov/15015546/