Artificial neural networks in problems of material objects implementation. Part 2. Design and application specifics

被引：0

作者：

Adamenko, V ^{[1
]}

Mirskykh, G. ^{[1
]}

机构：

[1] Natl Tech Univ Ukraine, Kyiv Polytech Inst, Kiev, Ukraine

来源：

VISNYK NTUU KPI SERIIA-RADIOTEKHNIKA RADIOAPARATOBUDUVANNIA | 2012年 / 48期

关键词：

artificial neural network; paradigms and rules of learning; approximation functions; neural networks ensembles;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this work paradigms and rules of neural networks learning are considered in a generalized form and the relationship between them are analyzed. The major tasks which can be solved by means of neural networks are analyzed. The main problem of using neural networks in problems of material objects implementation are defined in need of further theoretical research. The expediency of usage neural networks ensembles are substantiated with the followed by their transformation under specific applied design problems.

引用

页码：213 / 221

页数：9

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