The Parallel Approach to the Conjugate Gradient Learning Algorithm for the Feedforward Neural Networks

被引：28

作者：

Bilski, Jaroslaw ^{[1
]}

Smolag, Jacek ^{[1
]}

Galushkin, Alexander I. ^{[2
]}

机构：

[1] Czestochowa Tech Univ, Inst Computat Intelligence, Czestochowa, Poland

[2] Moscow Inst Phys & Technol, Moscow, Russia

来源：

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING ICAISC 2014, PT I | 2014年 / 8467卷

关键词：

REALIZATION;

D O I：

10.1007/978-3-319-07173-2_2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents the parallel architecture of the conjugate gradient learning algorithm for the feedforward neural networks. The proposed solution is based on the high parallel structures to speed up learning performance. Detailed parallel neural network structures are explicitly shown.

引用

页码：12 / 21

页数：10

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