Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates

Zhigang Zeng; Jun Wang

doi:10.1007/11759966_121

Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates

Zhigang Zeng
, Jun Wang

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

In this paper, discrete-time cellular neural networks with one-dimensional space invariant are designed to associative memories. The obtained results enable both heteroassociative and autoassociative memories to be synthesized by assuring the global asymptotic stability of the equilibrium point and the feeding data via external inputs rather than initial conditions. It is shown that criteria herein can ensure the designed input matrix to be obtained by using one-dimensional space-invariant cloning template. Finally, one specific example is included to demonstrate the applicability of the methodology. © Springer-Verlag Berlin Heidelberg 2006.

Original language	English
Title of host publication	Advances in Neural Networks - ISNN 2006
Subtitle of host publication	Third International Symposium on Neural Networks, ISNN 2006, Proceedings
Publisher	Springer Verlag
Pages	824-829
Volume	3971 LNCS
ISBN (Print)	354034439, 9783540344391
DOIs	https://doi.org/10.1007/11759966_121
Publication status	Published - 2006
Externally published	Yes
Event	3rd International Symposium on Neural Networks (ISNN 2006): Advances in Neural Networks - Chengdu, China Duration: 28 May 2006 → 1 Jun 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3971 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Symposium on Neural Networks (ISNN 2006)
Place	China
City	Chengdu
Period	28/05/06 → 1/06/06

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10.1007/11759966_121

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Zeng, Z., & Wang, J. (2006). Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates. In Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings (Vol. 3971 LNCS, pp. 824-829). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3971 LNCS). Springer Verlag. https://doi.org/10.1007/11759966_121

Zeng, Zhigang ; Wang, Jun. / Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates. Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings. Vol. 3971 LNCS Springer Verlag, 2006. pp. 824-829 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates",

abstract = "In this paper, discrete-time cellular neural networks with one-dimensional space invariant are designed to associative memories. The obtained results enable both heteroassociative and autoassociative memories to be synthesized by assuring the global asymptotic stability of the equilibrium point and the feeding data via external inputs rather than initial conditions. It is shown that criteria herein can ensure the designed input matrix to be obtained by using one-dimensional space-invariant cloning template. Finally, one specific example is included to demonstrate the applicability of the methodology. {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.",

author = "Zhigang Zeng and Jun Wang",

year = "2006",

doi = "10.1007/11759966\_121",

language = "English",

isbn = "354034439",

volume = "3971 LNCS",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "824--829",

booktitle = "Advances in Neural Networks - ISNN 2006",

address = "Germany",

note = "3rd International Symposium on Neural Networks (ISNN 2006) : Advances in Neural Networks ; Conference date: 28-05-2006 Through 01-06-2006",

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Zeng, Z & Wang, J 2006, Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates. in Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings. vol. 3971 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3971 LNCS, Springer Verlag, pp. 824-829, 3rd International Symposium on Neural Networks (ISNN 2006), Chengdu, China, 28/05/06. https://doi.org/10.1007/11759966_121

Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates. / Zeng, Zhigang; Wang, Jun.
Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings. Vol. 3971 LNCS Springer Verlag, 2006. p. 824-829 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3971 LNCS).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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N2 - In this paper, discrete-time cellular neural networks with one-dimensional space invariant are designed to associative memories. The obtained results enable both heteroassociative and autoassociative memories to be synthesized by assuring the global asymptotic stability of the equilibrium point and the feeding data via external inputs rather than initial conditions. It is shown that criteria herein can ensure the designed input matrix to be obtained by using one-dimensional space-invariant cloning template. Finally, one specific example is included to demonstrate the applicability of the methodology. © Springer-Verlag Berlin Heidelberg 2006.

AB - In this paper, discrete-time cellular neural networks with one-dimensional space invariant are designed to associative memories. The obtained results enable both heteroassociative and autoassociative memories to be synthesized by assuring the global asymptotic stability of the equilibrium point and the feeding data via external inputs rather than initial conditions. It is shown that criteria herein can ensure the designed input matrix to be obtained by using one-dimensional space-invariant cloning template. Finally, one specific example is included to demonstrate the applicability of the methodology. © Springer-Verlag Berlin Heidelberg 2006.

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U2 - 10.1007/11759966_121

DO - 10.1007/11759966_121

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 354034439

SN - 9783540344391

VL - 3971 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Zeng Z, Wang J. Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates. In Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings. Vol. 3971 LNCS. Springer Verlag. 2006. p. 824-829. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11759966_121

Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates

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