Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity.
about
An efficient coding hypothesis links sparsity and selectivity of neural responses.Bayesian cue integration as a developmental outcome of reward mediated learningNetwork evolution induced by asynchronous stimuli through spike-timing-dependent plasticitySpiking neuron network Helmholtz machine.Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.Self-organization of synchronous activity propagation in neuronal networks driven by local excitationPredicting non-linear dynamics by stable local learning in a recurrent spiking neural network.Effect of synaptic plasticity on the structure and dynamics of disordered networks of coupled neurons.Hardware-amenable structural learning for spike-based pattern classification using a simple model of active dendrites.
P2860
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P2860
Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity.
description
2010 nî lūn-bûn
@nan
2010 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Perceptron learning rule deriv ...... ike-time-dependent plasticity.
@ast
Perceptron learning rule deriv ...... ike-time-dependent plasticity.
@en
type
label
Perceptron learning rule deriv ...... ike-time-dependent plasticity.
@ast
Perceptron learning rule deriv ...... ike-time-dependent plasticity.
@en
prefLabel
Perceptron learning rule deriv ...... ike-time-dependent plasticity.
@ast
Perceptron learning rule deriv ...... ike-time-dependent plasticity.
@en
P2093
P2860
P356
P1476
Perceptron learning rule deriv ...... ike-time-dependent plasticity.
@en
P2093
Prashanth D'Souza
Richard H R Hahnloser
Shih-Chii Liu
P2860
P304
P356
10.1073/PNAS.0909394107
P407
P577
2010-02-18T00:00:00Z