Results 121 to 130 of about 68,442 (287)

Evolutionary spiking neural networks: a survey

Journal of Membrane Computing
Spiking neural networks (SNNs) are gaining increasing attention as potential computationally efficient alternatives to traditional artificial neural networks(ANNs). However, the unique information propagation mechanisms and the complexity of SNN neuron models pose challenges for adopting traditional methods developed for ANNs to SNNs.
Shuaijie Shen, Rui Zhang 0042, Chao Wang, Renzhuo Huang, Aiersi Tuerhong, Qinghai Guo, Zhichao Lu, Jianguo Zhang, Luziwei Leng   +8 more
openaire   +2 more sources

PolyGraph – Flexible, Biocompatible & Electrically Optimized Graphene‐Polymer Composites for Next‐Generation Neural Interfaces

Advanced Healthcare Materials, EarlyView.
PolyGraph, a flexible graphene‐polycaprolactone nanocomposite, unites conductivity, biocompatibility, and processability for next‐generation neural interfaces. Fabricated into microneedle arrays with ultra‐flexible backings, PolyGraph enables bidirectional neuronal recording and stimulation in brain tissue, advancing brain‐computer interface (BCI) and ...
Jack Maughan, Ian Woods, Cian O'Connor, Pablo Quintana‐Sarti, Eoin Caffrey, Jose M. Munuera, Tian Carey, Adrian Dervan, Alejandro López Valdés, Omar Mamad, Maeve A. Caldwell, Fergal J. O'Brien, Jonathan N. Coleman   +12 more
wiley   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Light‐Induced Entropy for Secure Vision

Advanced Materials, EarlyView.
This work realized a ternary true random number generator by exploiting stochastic traps emerging within multiple junction interfaces, and quantitatively validated the generation of high‐quality random numbers. Furthermore, it successfully demonstrated diverse applications, including AI‐resilient image security, thereby providing a valuable guide for ...
Juhyung Seo, Seungme Kang, Chaehyun Kim, Taehyun Park, Youngwoo Yoo, Yeong Kwon Kim, Wonjun Shin, Byung Chul Jang, Young‐Joon Kim, Hocheon Yoo   +9 more
wiley   +1 more source

Self‐Powered Flexible Triboelectric‐Gated Ion‐Gel Transistor for Neuromorphic Tactile Sensing and Human Activity Recognition

Advanced Materials, EarlyView.
A fully flexible ion‐gel‐gated graphene‐channel transistor driven by a triboelectric nanogenerator enables self‐powered tactile sensing and synaptic learning. Mimicking spike‐rate‐dependent plasticity, the device exhibits frequency‐selective potentiation and depression, supporting rate‐coded neuromorphic computation even under flex.
Hanseong Cho, Seoyeon Park, Youngmin Lee, Sejoon Lee   +3 more
wiley   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Wide learning: Using an ensemble of biologically-plausible spiking neural networks for unsupervised parallel classification of spatio-temporal patterns [PDF]

, 2018
Spiking neural networks have been previously used to perform tasks such as object recognition without supervision. One of the concerns relating to the spiking neural networks is their speed of operation and the number of iterations necessary to train and
Bentley, P, Kozdon, K
core  

Spiking Neural Network Pressure Sensor

Neural Computation
Abstract Von Neumann architecture requires information to be encoded as numerical values. For that reason, artificial neural networks running on computers require the data coming from sensors to be discretized. Other network architectures that more closely mimic biological neural networks (e.g., spiking neural networks) can be simulated ...
Michal Markiewicz, Ireneusz Brzozowski, Szymon Janusz   +2 more
openaire   +3 more sources

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source