Neural network model of hysteresis

J. D. Wei; C. T. Sun

Neural network model of hysteresis

J. D. Wei^*
, C. T. Sun

^*Corresponding author for this work

National Yang Ming Chiao Tung University

Research output: Contribution to conference › Conference Paper › peer-review

2 Scopus citations

Abstract

Hysteresis is an effect of memory, which is frequently observed in the realm of nature. The purpose of this paper is trying to understand more of it, such that we may achieve better performance from the systems which are hysteresis-embedded. A hypothesis-based neural network model is offered in this paper. We name it the Synchronous Delay Network (SDN) model. It can be realized as a feed-forward neural network. We also discuss the possible applications in this paper.

Original language	English
Pages	412-417
Number of pages	6
State	Published - 1996
Externally published	Yes
Event	Proceedings of the 1996 Asian Fuzzy Systems Symposium - Kenting, Taiwan Duration: 11 12 1996 → 14 12 1996

Conference

Conference	Proceedings of the 1996 Asian Fuzzy Systems Symposium
City	Kenting, Taiwan
Period	11/12/96 → 14/12/96

Cite this

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title = "Neural network model of hysteresis",

abstract = "Hysteresis is an effect of memory, which is frequently observed in the realm of nature. The purpose of this paper is trying to understand more of it, such that we may achieve better performance from the systems which are hysteresis-embedded. A hypothesis-based neural network model is offered in this paper. We name it the Synchronous Delay Network (SDN) model. It can be realized as a feed-forward neural network. We also discuss the possible applications in this paper.",

author = "Wei, \{J. D.\} and Sun, \{C. T.\}",

year = "1996",

language = "英语",

pages = "412--417",

note = "Proceedings of the 1996 Asian Fuzzy Systems Symposium ; Conference date: 11-12-1996 Through 14-12-1996",

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TY - CONF

T1 - Neural network model of hysteresis

AU - Wei, J. D.

AU - Sun, C. T.

PY - 1996

Y1 - 1996

N2 - Hysteresis is an effect of memory, which is frequently observed in the realm of nature. The purpose of this paper is trying to understand more of it, such that we may achieve better performance from the systems which are hysteresis-embedded. A hypothesis-based neural network model is offered in this paper. We name it the Synchronous Delay Network (SDN) model. It can be realized as a feed-forward neural network. We also discuss the possible applications in this paper.

AB - Hysteresis is an effect of memory, which is frequently observed in the realm of nature. The purpose of this paper is trying to understand more of it, such that we may achieve better performance from the systems which are hysteresis-embedded. A hypothesis-based neural network model is offered in this paper. We name it the Synchronous Delay Network (SDN) model. It can be realized as a feed-forward neural network. We also discuss the possible applications in this paper.

UR - https://www.scopus.com/pages/publications/0030365117

M3 - 论文

AN - SCOPUS:0030365117

SP - 412

EP - 417

T2 - Proceedings of the 1996 Asian Fuzzy Systems Symposium

Y2 - 11 December 1996 through 14 December 1996

ER -

Neural network model of hysteresis

Abstract

Conference

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Cite this