Introduction to the Special Issue on G-Networks and the Random Neural Network

被引：0

作者：

Gelenbe, Erol ^{[1
]}

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Dept Elect & Elect Engn, London SW7 2BT, England

来源：

PERFORMANCE EVALUATION | 2011年 / 68卷 / 04期

关键词：

D O I：

10.1016/j.peva.2011.02.004

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This special issue includes seven papers on G-networks and the Random Neural Network (RNN), approximately twenty years after these models were first introduced. We summarise the differences between the research trends related to these two branches of the same initial model, and point to applications that are less known to the Performance community and suggest significant questions related to G-networks and the RNN that are fruitful research directions. (C) 2011 Published by Elsevier B.V.

引用

页码：307 / 308

页数：2

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