Hammerstein-Wiener Model: A New Approach to the Estimation of Formal Neural Information

被引：0

作者：

Abbasi-Asl, Reza ^{[1
]}

Khorsandi, Rahman ^{[2
]}

Vosooghi-Vahdat, Bijan ^{[1
]}

机构：

[1] Sharif Univ Technol, Sch Elect Engn, Biomed Signal & Image Proc Lab BiSIPL, POB 11356-9363, Tehran, Iran

[2] Univ Miami, Dept Elect & Comp Engn, Coral Gables, FL 33124 USA

来源：

BASIC AND CLINICAL NEUROSCIENCE | 2012年 / 3卷 / 04期

关键词：

Formal Information Estimation; Neurons; Hammerstein-Wiener Model;

D O I：

暂无

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

A new approach is introduced to estimate the formal information of neurons. Formal Information, mainly discusses about the aspects of the response that is related to the stimulus. Estimation is based on introducing a mathematical nonlinear model with Hammerstein-Wiener system estimator. This method of system identification consists of three blocks to completely describe the nonlinearity of input and output and linear behaviour of the model. The introduced model is trained by 166 spikes of neurons and other 166 spikes are used to test and validate the model. The simulation results show the R-Value of 92.6 % between estimated and reference information rate. This shows improvement of 1.41 % in comparison with MLP neural network.

引用

页码：45 / 51

页数：7

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