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Indexed by:期刊论文

Date of Publication:2012-10-01

Journal:NEURAL PROCESSING LETTERS

Included Journals:SCIE、EI、Scopus

Volume:36

Issue:2

Page Number:135-144

ISSN No.:1370-4621

Key Words:Spiking neuron; Firing time; Derivative of the state function

Abstract:In usual spiking neural networks, the real world information is interpreted as spike time. A spiking neuron of the spiking neural network receives input vector of spike times, and activates a state function x(t) by increasing the time t until the value of x(t) reaches certain threshold value at a firing time t (a) . And t (a) is the output of the spiking neuron. In this paper we propose, and investigate the performance of, a modified spiking neuron, of which the output is a linear combination of the firing time t (a) and the derivative x'(t (a) ). The merit of the modified spiking neuron is shown by numerical experiments for solving some benchmark problems: The computational time of a modified spiking neuron is a little greater than that of a usual spiking neuron, but the accuracy of a modified spiking neuron is almost as good as a usual spiking neural network with a hidden layer.