PARALLEL IMPLEMENTATION AND CAPABILITIES OF ENTROPY-DRIVEN ARTIFICIAL NEURAL NETWORKS

被引：2

作者：

TOLLENAERE, T ^{[1
]}

VANHULLE, MM ^{[1
]}

ORBAN, GA ^{[1
]}

机构：

[1] KATHOLIEKE UNIV LEUVEN,DEPT ELECTROTECH,DIV ESAT,B-3001 HEVERLEE,BELGIUM

来源：

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING | 1992年 / 14卷 / 03期

基金：

英国医学研究理事会;

关键词：

D O I：

10.1016/0743-7315(92)90069-Y

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

It is shown how the recently introduced Entropy-Driven Artificial Neural Network Model (EDANN) can be implemented on a parallel transputer array, using a simulation environment which makes all decomposition and mapping issues transparent. Then, using the parallel simulator, the EDANN's capabilities are exemplified in the case of orientation extraction from retinal images. By means of simulations on the parallel machine, it is shown that the EDANN is able to adapt itself optimally to the stimulus it receives, and that the same network topology is able to accomplish both 1-D and 2-D orientation inference tasks. © 1992.

引用

页码：286 / 305

页数：20

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