Results 101 to 110 of about 10,988 (267)

Reinforced liquid state machines—new training strategies for spiking neural networks based on reinforcements

Frontiers in Computational Neuroscience
IntroductionFeedback and reinforcement signals in the brain act as natures sophisticated teaching tools, guiding neural circuits to self-organization, adaptation, and the encoding of complex patterns.
Dominik Krenzer, Martin Bogdan, Martin Bogdan, Martin Bogdan   +3 more
doaj   +1 more source

Optoelectronic Nanofluidic Neural Networks for Ionic Computing

Advanced Materials, EarlyView.
An ion‐based optoelectronic nanofluidic memristor enables neuromorphic computing in aqueous environments. With tunable ionic memory and multimodal synaptic plasticity, it realizes densely connected ionic neural networks capable of image classification, motion prediction, logic computation, and real‐time in‐sensor computing, advancing fully connected ...
Yaxin Huang, Zhiyuan Du, Changjin Wu, Binglin Zeng, Yingnan Cao, Mingliang Li, Liren Zhang, Qingxin Guo, Chao Huang, Can Li, Jinyao Tang   +10 more
wiley   +1 more source

Electrically Coded Retinomorphic Spectrophotodetector

Advanced Materials, EarlyView.
Self‐powered retinomorphic pyro‐photodetector is demonstrated that avoids machine‐learning post‐processing and covers 365–940 nm. Electrostatic balancing of built‐in potential produces an electrical wavelength code, delivering <3 nm wavelength decoding accuracy with ∼46 µs response.
Mohit Kumar, Hyunmin Dang, Hyungtak Seo
wiley   +1 more source

Charge‐Encoded Sidechains Enable Deterministic Ion Ingress and Memory Retention in Organic Electrochemical Synaptic Transistors

Advanced Materials, EarlyView.
Organic electrochemical synaptic transistors based on sidechain‐engineered conjugated polyelectrolytes reveal that cationic sidechains enable efficient volumetric ion penetration and dense backbone doping, leading to enhanced transconductance and long‐term synaptic retention.
Haim Kwon, Jihyeon You, Chaeyeon Park, Dong Gue Roe, Ji Hyun Jung, Jeong Ho Cho, Han Young Woo   +6 more
wiley   +1 more source

Characterization of a Spiking Convolutional Processor for FPGA

Sensors
In event-based neuromorphic processing, computer vision finds an efficient alternative capable of optimizing computational and energy resources, inspired by the dynamics of biological neural systems. In the development of real-time processing systems, it
Dagnier A. Curra-Sosa, Francisco Gomez-Rodriguez, Alejandro Linares-Barranco   +2 more
doaj   +1 more source

Metal Oxide Nano‐Interface Boosting the Deep Ultraviolet Adjustable Noise‐Filtering In‐Sensor Computing

Advanced Materials, EarlyView.
We show that sol‐gel‐fractured indium–magnesium oxide combines deep‐ultraviolet responsivity, high carrier mobility, and an excellent memory dynamic range. This unique materials platform enables deep‐ultraviolet long‐afterglow light‐emitting devices with multifunctional integration.
Zhongshi Ju, Peng Li, Jingsong Yuan, Boyuan Yu, Bin Han, Yusheng Chen, Jiangang Ma, Haiyang Xu, Yichun Liu, Paolo Samorì   +9 more
wiley   +1 more source

Integrating computational modeling, neuroimaging, and neuromodulation to decompose perceptual decision-making in healthy aging: a review of methods, findings, and gaps

Frontiers in Aging Neuroscience
Perceptual decision-making (PDM) — the transformation of sensory input into behavioral choice — declines with healthy aging, leading to slower responses, altered accuracy, and negative impacts on quality of life.
Anna Udoratina, Anna Udoratina, Vladimir Maksimenko, Vladimir Maksimenko, Susanna Gordleeva, Susanna Gordleeva, Susanna Gordleeva   +6 more
doaj   +1 more source

Noise‐Tunable Memristor Enabling Programmable Probabilistic Neurons for Frequency‐Selective Time‐Series Signal Encoding

Advanced Materials, EarlyView.
Memristors offer tunable resistance and intrinsic instability, making them promising tunable noise sources. We propose a spiking‐rate‐programmable probabilistic neuron using a Ru/TaOx/Pt memristor, where resistance‐dependent noise enables frequency‐selective encoding.
Do Hoon Kim, Seoeun Jang, Hakseung Rhee, Min Gu Lee, Daehee Kim, Taewook Go, Woon Hyung Cheong, Hanchan Song, Kyung Min Kim   +8 more
wiley   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing

Neuromorphic Computing and Engineering
In this work, we demonstrate the potential of HfO₂-based memristors as artificial synapses capable of reproducing biologically plausible spike-timing-dependent plasticity (STDP).
Mostafa Shooshtari, Saeideh Pahlavan, Teresa Serrano Gotarredona, Bernabé Linares-Barranco   +3 more
doaj   +1 more source