Finite Impulse Response (FIR) Filter Model of Synapses: Associated Neural Networks

被引：3
|
作者：
Garimella, Rama Murthy [1 ]
机构：
[1] Commun & Networking Res Ctr, Int Inst Informat Technol, Hyderabad 500032, Andhra Pradesh, India
来源：
ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 2, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/ICNC.2008.910
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this research paper, based on biological motivation, synapse is modeled as a Finite Impulse Response (FIR) linear filter. Motivation for the concept of robust neural networks is proposed. A novel incremental gradient based learning algorithm is derived (to update the FIR filter coefficients in successive slots). This model of neuron is utilized for arriving at a multi-layer perceptron. Also, a potential associative memory based on FIR filter model of synapse is proposed. Briefly the novel model of neuron is compared with the traditional model of neuron It is reasoned that the traditional model of a neuron is very restrictive.
引用
收藏
页码：370 / 374
页数：5
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