Statistical Information Based Single Neuron Adaptive Control for Non-Gaussian Stochastic Systems

Statistical Information Based Single Neuron Adaptive Control for Non-Gaussian Stochastic Systems

Based on information theory, the single neuron adaptive control problem for stochastic systems with non-Gaussian noises is investigated in this paper. Here, the statistic information of the output within a receding window rather than the output value is used for the tracking problem. Firstly, the si...

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Bibliographic Details
Main Authors: Guolian Hou, Ye Tian, Man Jiang, Jianhua Zhang, Mifeng Ren
Format: Article
Language:English
Published: MDPI AG 2012-07-01
Series:Entropy
Subjects:
statistic information
single neuron adaptive control
non-Gaussian
minimum entropy
Online Access:http://www.mdpi.com/1099-4300/14/7/1154

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