Results 71 to 80 of about 76,325 (312)
A Synaptic Pruning-Based Spiking Neural Network for Hand-Written Digits Classification
Frontiers in Artificial Intelligence, 2022 A spiking neural network model inspired by synaptic pruning is developed and trained to extract features of hand-written digits. The network is composed of three spiking neural layers and one output neuron whose firing rate is used for classification ...
Faramarz Faghihi +3 more
doaj +1 more source
, 2017 Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural networks is the vector-matrix multiply when inputs are multiplied by the neural ...
Aimone, James B. +9 more
core +1 more source
Advanced Functional Materials, EarlyView.A frequency‐tunable ferroelectric synaptic transistor based on a buried‐gate InGaZnO channel and Al2O3/HfO2 dielectric stack exhibits linear and reversible weight updates using single‐polarity pulses. By switching between ferroelectric and trap‐assisted modes depending on input frequency, the device simplifies neuromorphic circuit design and achieves ...
Ojun Kwon +8 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Multicolor optoelectronic synapses are realized by vertically integrating solution‐processed MoS2 thin‐film and SWCNT. The electronically disconnected but interactive MoS2 enables photon‐modulated remote doping, producing a bi‐directional photoresponse.
Jihyun Kim +8 more
wiley +1 more source
Sound Recognition System Using Spiking and MLP Neural Networks [PDF]
, 2016 In this paper, we explore the capabilities of a sound classification system that combines a Neuromorphic Auditory System for feature extraction and an artificial neural network for classification.
Cerezuela Escudero, Elena +5 more
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Modeling spiking neural networks
Theoretical Computer Science, 2008 AbstractA notation for the functional specification of a wide range of neural networks consisting of temporal or non-temporal neurons, is proposed. The notation is primarily a mathematical framework, but it can also be illustrated graphically and can be extended into a language in order to be automated. Its basic building blocks are processing entities,
Zaharakis, Ioannis D. +1 more
openaire +1 more source
Near‐Infrared Organic Photovoltaic Electrodes for Subretinal Neurostimulation
Advanced Functional Materials, EarlyView.Organic photovoltaic electrodes based on the D18:Y6 blend enable precise and light‐controlled activation of retinal ganglion cells in a degenerating retina. NIR Light‐driven activation of retinal ganglion cells, tunable stimulation parameters, and biocompatibility with human retinal organoids highlight their potential for next‐generation prosthetics ...
Andrea Corna +10 more
wiley +1 more source
BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python
Frontiers in Neuroinformatics, 2018 The development of spiking neural network simulation software is a critical component enabling the modeling of neural systems and the development of biologically inspired algorithms.
Hananel Hazan +6 more
doaj +1 more source
A Spiking Neuron and Population Model Based on the Growth Transform Dynamical System
Frontiers in Neuroscience, 2020 In neuromorphic engineering, neural populations are generally modeled in a bottom-up manner, where individual neuron models are connected through synapses to form large-scale spiking networks.
Ahana Gangopadhyay +2 more
doaj +1 more source
Self-Learning Fuzzy Spiking Neural Network as a Nonlinear Pulse-Position Threshold Detection Dynamic System Based on Second-Order Critically Damped Response Units [PDF]
, 2009 Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered.
Bodyanskiy, Yevgeniy +2 more
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