DocumentCode :
527871
Title :
The non-linear properties of Spike-Rate Perceptron with sub-Poisson input
Author :
Xiang, Xuyan ; Deng, Yingchun ; Yang, Xiangqun
Author_Institution :
Coll. of Math. & Comput. Sci., Hunan Univ. of Arts & Sci., Changde, China
Volume :
4
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1974
Lastpage :
1978
Abstract :
We present more specific non-linear properties of Spike-Rate Perceptron with sub-Poisson inputs based on the diffusion approximation of renewal process, which employs both first and second statistical representation, i.e. the means, variances and correlations of the synaptic input. It shows that such perceptron is also able to perform various complex non-linear tasks, and to successfully solve the XOR problem. Here such perceptron offers the same advantage that includes both the mean and the variance of the input signal as Spike-Rate Perceptron.
Keywords :
Poisson distribution; approximation theory; perceptrons; statistical analysis; XOR problem; diffusion approximation; spike-rate perceptron nonlinear properties; statistical representation; subPoisson input; Approximation methods; Biological system modeling; Computational modeling; Correlation; Equations; Mathematical model; Neurons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5584714
Filename :
5584714
Link To Document :
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