Passivity-based control for Hopfield neural networks using convex representation

D. H. Ji; J. H. Koo; S. C. Won; S. M. Lee; Ju H. Park

doi:10.1016/j.amc.2010.12.100

Passivity-based control for Hopfield neural networks using convex representation

D. H. Ji
, J. H. Koo
, S. C. Won
, S. M. Lee
, Ju H. Park

School of Electronics Engineering

Samsung
Pohang University of Science and Technology
Yeungnam University

Research output: Contribution to journal › Article › peer-review

64 Scopus citations

Abstract

This paper considers the problem of passivity-based controller design for Hopfield neural networks. By making use of a convex representation of nonlinearities, a feedback control scheme based on passivity and Lyapunov theory is presented. A criterion for existence of the controller is given in terms of linear matrix inequality (LMI), which can be easily solved by a convex optimization problem. An example and its numerical simulation are given to show the effectiveness of the proposed method.

Original language	English
Pages (from-to)	6168-6175
Number of pages	8
Journal	Applied Mathematics and Computation
Volume	217
Issue number	13
DOIs	https://doi.org/10.1016/j.amc.2010.12.100
State	Published - 1 Mar 2011

Keywords

Convex problem
H passivity
Hopfield neural network
LMI

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10.1016/j.amc.2010.12.100

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abstract = "This paper considers the problem of passivity-based controller design for Hopfield neural networks. By making use of a convex representation of nonlinearities, a feedback control scheme based on passivity and Lyapunov theory is presented. A criterion for existence of the controller is given in terms of linear matrix inequality (LMI), which can be easily solved by a convex optimization problem. An example and its numerical simulation are given to show the effectiveness of the proposed method.",

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AU - Won, S. C.

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AU - Park, Ju H.

PY - 2011/3/1

Y1 - 2011/3/1

N2 - This paper considers the problem of passivity-based controller design for Hopfield neural networks. By making use of a convex representation of nonlinearities, a feedback control scheme based on passivity and Lyapunov theory is presented. A criterion for existence of the controller is given in terms of linear matrix inequality (LMI), which can be easily solved by a convex optimization problem. An example and its numerical simulation are given to show the effectiveness of the proposed method.

AB - This paper considers the problem of passivity-based controller design for Hopfield neural networks. By making use of a convex representation of nonlinearities, a feedback control scheme based on passivity and Lyapunov theory is presented. A criterion for existence of the controller is given in terms of linear matrix inequality (LMI), which can be easily solved by a convex optimization problem. An example and its numerical simulation are given to show the effectiveness of the proposed method.

KW - Convex problem

KW - H passivity

KW - Hopfield neural network

KW - LMI

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ER -

Passivity-based control for Hopfield neural networks using convex representation

Abstract

Keywords

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