Chaos synchronization of coupled neurons via H-infinity control with cooperative weights neural network

Yuliang Liu; Ruixue Li; Yanqiu Che; Chunxiao Han

doi:10.1007/978-3-642-29390-0_59

Chaos synchronization of coupled neurons via H-infinity control with cooperative weights neural network

Yuliang Liu, Ruixue Li, Yanqiu Che, Chunxiao Han

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

In this paper, an H-infinity control with a cooperative weights neural network is proposed to realize the synchronization of two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons. We first use a cooperative weights neural network to approximate the unknown nonlinear function. Then we employ the H-infinity control technique to attenuate the effects caused by unmodelled dynamics, disturbances and approximate errors. Finally, by Lyapunov method, the overall closed-loop system is shown to be stable and chaos synchronization is obtained. The control scheme is robust to the uncertainties such as unmodelled dynamics, ionic channel noises and external disturbances. The simulation results demonstrate the effectiveness of the proposed control method.

Original language	English (US)
Title of host publication	Advances in Future Computerand Control Systems
Pages	369-374
Number of pages	6
Edition	VOL. 2
DOIs	https://doi.org/10.1007/978-3-642-29390-0_59
State	Published - May 18 2012
Event	Future Computer and Control Systems, FCCS 2012 - Changsha, China Duration: Apr 21 2012 → Apr 22 2012

Publication series

Name	Advances in Intelligent and Soft Computing
Number	VOL. 2
Volume	160 AISC
ISSN (Print)	1867-5662

Other

Other	Future Computer and Control Systems, FCCS 2012
Country/Territory	China
City	Changsha
Period	4/21/12 → 4/22/12

All Science Journal Classification (ASJC) codes

General Computer Science

Access to Document

10.1007/978-3-642-29390-0_59

Cite this

@inproceedings{d3b6b5e2078247fa81efcadf4f70d723,

title = "Chaos synchronization of coupled neurons via H-infinity control with cooperative weights neural network",

abstract = "In this paper, an H-infinity control with a cooperative weights neural network is proposed to realize the synchronization of two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons. We first use a cooperative weights neural network to approximate the unknown nonlinear function. Then we employ the H-infinity control technique to attenuate the effects caused by unmodelled dynamics, disturbances and approximate errors. Finally, by Lyapunov method, the overall closed-loop system is shown to be stable and chaos synchronization is obtained. The control scheme is robust to the uncertainties such as unmodelled dynamics, ionic channel noises and external disturbances. The simulation results demonstrate the effectiveness of the proposed control method.",

author = "Yuliang Liu and Ruixue Li and Yanqiu Che and Chunxiao Han",

year = "2012",

month = may,

day = "18",

doi = "10.1007/978-3-642-29390-0_59",

language = "English (US)",

isbn = "9783642293894",

series = "Advances in Intelligent and Soft Computing",

number = "VOL. 2",

pages = "369--374",

booktitle = "Advances in Future Computerand Control Systems",

edition = "VOL. 2",

note = "Future Computer and Control Systems, FCCS 2012 ; Conference date: 21-04-2012 Through 22-04-2012",

}

Liu, Y, Li, R, Che, Y & Han, C 2012, Chaos synchronization of coupled neurons via H-infinity control with cooperative weights neural network. in Advances in Future Computerand Control Systems. VOL. 2 edn, Advances in Intelligent and Soft Computing, no. VOL. 2, vol. 160 AISC, pp. 369-374, Future Computer and Control Systems, FCCS 2012, Changsha, China, 4/21/12. https://doi.org/10.1007/978-3-642-29390-0_59

Chaos synchronization of coupled neurons via H-infinity control with cooperative weights neural network. / Liu, Yuliang; Li, Ruixue; Che, Yanqiu et al.
Advances in Future Computerand Control Systems. VOL. 2. ed. 2012. p. 369-374 (Advances in Intelligent and Soft Computing; Vol. 160 AISC, No. VOL. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Chaos synchronization of coupled neurons via H-infinity control with cooperative weights neural network

AU - Liu, Yuliang

AU - Li, Ruixue

AU - Che, Yanqiu

AU - Han, Chunxiao

PY - 2012/5/18

Y1 - 2012/5/18

N2 - In this paper, an H-infinity control with a cooperative weights neural network is proposed to realize the synchronization of two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons. We first use a cooperative weights neural network to approximate the unknown nonlinear function. Then we employ the H-infinity control technique to attenuate the effects caused by unmodelled dynamics, disturbances and approximate errors. Finally, by Lyapunov method, the overall closed-loop system is shown to be stable and chaos synchronization is obtained. The control scheme is robust to the uncertainties such as unmodelled dynamics, ionic channel noises and external disturbances. The simulation results demonstrate the effectiveness of the proposed control method.

AB - In this paper, an H-infinity control with a cooperative weights neural network is proposed to realize the synchronization of two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons. We first use a cooperative weights neural network to approximate the unknown nonlinear function. Then we employ the H-infinity control technique to attenuate the effects caused by unmodelled dynamics, disturbances and approximate errors. Finally, by Lyapunov method, the overall closed-loop system is shown to be stable and chaos synchronization is obtained. The control scheme is robust to the uncertainties such as unmodelled dynamics, ionic channel noises and external disturbances. The simulation results demonstrate the effectiveness of the proposed control method.

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DO - 10.1007/978-3-642-29390-0_59

M3 - Conference contribution

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SN - 9783642293894

T3 - Advances in Intelligent and Soft Computing

SP - 369

EP - 374

BT - Advances in Future Computerand Control Systems

T2 - Future Computer and Control Systems, FCCS 2012

Y2 - 21 April 2012 through 22 April 2012

ER -

Chaos synchronization of coupled neurons via H-infinity control with cooperative weights neural network

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