11152206

Source:http://linkedlifedata.com/resource/pubmed/id/11152206

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0205360, umls-concept:C0205421, umls-concept:C0870951, umls-concept:C0936012, umls-concept:C2348867
pubmed:issue	7
pubmed:dateCreated	2001-1-9
pubmed:abstractText	In this paper, without assuming the boundedness, monotonicity and differentiability of the activation functions, we present new conditions ensuring existence, uniqueness, and global asymptotical stability of the equilibrium point of Hopfield neural network models with fixed time delays or distributed time delays. The results are applicable to both symmetric and nonsymmetric interconnection matrices, and all continuous nonmonotonic neuron activation functions.
pubmed:commentsCorrections	http://linkedlifedata.com/resource/pubmed/commentcorrection/11152206-12425445, http://linkedlifedata.com/resource/pubmed/commentcorrection/11152206-12425446
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/8805018
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Sep
pubmed:issn	0893-6080
pubmed:author	pubmed-author:JinXX, pubmed-author:ZhangJJ
pubmed:issnType	Print
pubmed:volume	13
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	745-53
pubmed:dateRevised	2006-11-15
pubmed:meshHeading	pubmed-meshheading:11152206-Algorithms, pubmed-meshheading:11152206-Neural Networks (Computer)
pubmed:year	2000
pubmed:articleTitle	Global stability analysis in delayed Hopfield neural network models.
pubmed:affiliation	Traction Power National Laboratory, Southwest Jiaotong University, Chengdu, People's Republic of China. jyzhang@home.swjtu.edu.cn
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't