Algebraic conditions of stability for Hopfield neural network

Xiaoxin Liao; Xuerong Mao; Jun Wang; Zhigang Zeng

doi:10.1360/02yf0206

Algebraic conditions of stability for Hopfield neural network

Xiaoxin Liao
, Xuerong Mao
, Jun Wang
, Zhigang Zeng

Research output: Journal Publications and Reviews › RGC 62 - Review of books or of software (or similar publications/items) › peer-review

5 Citations (Scopus)

Abstract

Using the relationship between the resistance, capacitance and current in Hopfield neural network, and the properties of sigmoid function, this paper gives the terse, explicit algebraical criteria of global exponential stability, global asymptotical stability and instability. Then this paper makes clear the essence of the stability that Hopfield defined, and provides a theoretical foundation for the design of a network. Copyright by Science in China Press 2004.

Original language	English
Pages (from-to)	113-125
Journal	Science in China, Series F: Information Sciences
Volume	47
Issue number	1
DOIs	https://doi.org/10.1360/02yf0206
Publication status	Published - Feb 2004
Externally published	Yes

Research Keywords

Activation function
Hopfield neural network
Physical parameter
Stability

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title = "Algebraic conditions of stability for Hopfield neural network",

abstract = "Using the relationship between the resistance, capacitance and current in Hopfield neural network, and the properties of sigmoid function, this paper gives the terse, explicit algebraical criteria of global exponential stability, global asymptotical stability and instability. Then this paper makes clear the essence of the stability that Hopfield defined, and provides a theoretical foundation for the design of a network. Copyright by Science in China Press 2004.",

keywords = "Activation function, Hopfield neural network, Physical parameter, Stability",

author = "Xiaoxin Liao and Xuerong Mao and Jun Wang and Zhigang Zeng",

year = "2004",

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doi = "10.1360/02yf0206",

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volume = "47",

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journal = "Science in China, Series F: Information Sciences",

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TY - JOUR

T1 - Algebraic conditions of stability for Hopfield neural network

AU - Liao, Xiaoxin

AU - Mao, Xuerong

AU - Wang, Jun

AU - Zeng, Zhigang

PY - 2004/2

Y1 - 2004/2

N2 - Using the relationship between the resistance, capacitance and current in Hopfield neural network, and the properties of sigmoid function, this paper gives the terse, explicit algebraical criteria of global exponential stability, global asymptotical stability and instability. Then this paper makes clear the essence of the stability that Hopfield defined, and provides a theoretical foundation for the design of a network. Copyright by Science in China Press 2004.

AB - Using the relationship between the resistance, capacitance and current in Hopfield neural network, and the properties of sigmoid function, this paper gives the terse, explicit algebraical criteria of global exponential stability, global asymptotical stability and instability. Then this paper makes clear the essence of the stability that Hopfield defined, and provides a theoretical foundation for the design of a network. Copyright by Science in China Press 2004.

KW - Activation function

KW - Hopfield neural network

KW - Physical parameter

KW - Stability

UR - https://www.scopus.com/pages/publications/24944463751

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-24944463751&origin=recordpage

U2 - 10.1360/02yf0206

DO - 10.1360/02yf0206

M3 - RGC 62 - Review of books or of software (or similar publications/items)

SN - 1009-2757

VL - 47

SP - 113

EP - 125

JO - Science in China, Series F: Information Sciences

JF - Science in China, Series F: Information Sciences

IS - 1

ER -

Algebraic conditions of stability for Hopfield neural network

Abstract

Research Keywords

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