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New critical analysis on global convergence of recurrent neural networks with projection mappings

  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

7 引用 (Scopus)

摘要

In this paper, we present the general analysis of global convergence for the recurrent neural networks (RNNs) with projection mappings in the critical case that M(L, Γ), a matrix related with the weight matrix W and the activation mapping of the networks, is nonnegative for a positive diagonal matrix Γ. In contrast to the existing conclusion such as in [1], the present critical stability results do not require the condition that ΓW must be symmetric and can be applied to the general projection mappings other than nearest point projection mappings. An example has also been shown that the theoretical results obtained in the present paper have explicitly practical application.

源语言英语
主期刊名Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
出版商Springer Verlag
131-139
页数9
版本PART 3
ISBN(印刷版)9783540723943
DOI
出版状态已出版 - 2007
活动4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, 中国
期限: 3 6月 20077 6月 2007

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
编号PART 3
4493 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议4th International Symposium on Neural Networks, ISNN 2007
国家/地区中国
Nanjing
时期3/06/077/06/07

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