Results 101 to 110 of about 68,095 (317)

Enhancing Synaptic Plasticity and Multistate Retention of Organic Neuromorphic Devices Using Anion‐Excessive Gel Electrolyte

Advanced Functional Materials, EarlyView.
Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won, Jeongwoo Lee, Hyunwook Kim, Joon Hak Oh   +3 more
wiley   +1 more source

Research on SNN Learning Algorithms and Networks Based on Biological Plausibility

IEEE Access
Spiking Neural Networks, inspired by the brain’s neuronal information processing mech- anisms, utilize sparse, event-based spike signals to emulate biological computation.
Bingqiang Huo, Fang Li, Siyu Peng, Hongwei Chen, Sudan Xin, Hongjun Wang   +5 more
doaj   +1 more source

Spiking Neural Network Decision Feedback Equalization for IM/DD Systems [PDF]

, 2023
Alexander von Bank, Eike-Manuel Edelmann, Laurent Schmalen   +2 more
openalex   +1 more source

Unsupervised Learning with Self-Organizing Spiking Neural Networks

, 2018
We present a system comprising a hybridization of self-organized map (SOM) properties with spiking neural networks (SNNs) that retain many of the features of SOMs.
Hazan, Hananel, Kozma, Robert, Sanghavi, Darpan T., Saunders, Daniel J., Siegelmann, Hava T.   +4 more
core   +1 more source

Conductance‐Dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing

Advanced Functional Materials, EarlyView.
A nanoscale SrTiO3 memristor is shown to exhibit dynamic synaptic behavior through the interaction of local electrical and global optical signals. Its photoresponse depends quantitatively on the conductance state, which evolves and decays over tunable timescales, enabling ultralow‐power, biorealistic learning mechanisms for advanced in‐memory and ...
Christoph Weilenmann, Hanglin He, Marko Mladenović, Till Zellweger, Kevin Portner, Klemens Bauer, Guillaume Bellec, Mathieu Luisier, Alexandros Emboras   +8 more
wiley   +1 more source

A neural circuit for navigation inspired by C. elegans Chemotaxis [PDF]

, 2014
We develop an artificial neural circuit for contour tracking and navigation inspired by the chemotaxis of the nematode Caenorhabditis elegans. In order to harness the computational advantages spiking neural networks promise over their non-spiking ...
Rajendran, Bipin, Santurkar, Shibani
core  

Simulation of networks of spiking neurons: A review of tools and strategies

, 2007
We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented.
Beeman, D., Boustani, S. El, Bower, J. M., Brette, R., Carnevale, T., Davison, A. P., Destexhe, A., Diesmann, M., Djurfeldt, M., Ermentrout, B., Goodman, P. H., Harris Jr., F. C., Hines, M., Lansner, A., Morrison, A., Muller, E., Natschlager, T., Pecevski, D., Rochel, O., Rudolph, M., Vieville, T., Zirpe, M.   +21 more
core   +3 more sources

Membrane Fusion‐Inspired Nanomaterials: Emerging Strategies for Infectious Disease and Cancer Diagnostics

Advanced Healthcare Materials, EarlyView.
Membrane fusion‐inspired nanomaterials offer transformative potential in diagnostics by mimicking natural fusion processes to achieve highly sensitive and specific detection of disease biomarkers. This review highlights recent advancements in nanomaterial functionalization strategies, signal amplification systems, and stimuli‐responsive fusion designs,
Sojeong Lee, Khulan Nyamzaya, Jueun Han, Yejin Song, Jihee Lee, Jung Hyun Jo, Seungmin Bang, Eun‐Kyung Lim, Seungjoo Haam, Eunjung Kim   +9 more
wiley   +1 more source

Fast learning without synaptic plasticity in spiking neural networks

Scientific Reports
Spiking neural networks are of high current interest, both from the perspective of modelling neural networks of the brain and for porting their fast learning capability and energy efficiency into neuromorphic hardware. But so far we have not been able to
Anand Subramoney, Guillaume Bellec, Franz Scherr, Robert Legenstein, Wolfgang Maass   +4 more
doaj   +1 more source

Assessing ECG Interpretation Expertise in Medical Practitioners Through Eye Movement Data and Neuromorphic Models

IEEE Access
This study introduces an innovative method for assessing ECG interpretation abilities in medical professionals via eye-tracking data. We examine eye movement patterns from five separate groups of cardiology practitioners utilizing a combination of ...
Syed Mohsin Bokhari, Muhammad Shafi, Fazal Noor, Sarmad Sohaib, Saad Alqahtany, Mark Donnelly   +5 more
doaj   +1 more source