Adaptive feedback control of chaotic neurodynamics in analog circuits

Hiroyasu Ando; Aki Nakano; Yoshihiko Horio; Kazuyuki Aihara

doi:10.1109/ISCAS.2009.5118339

Adaptive feedback control of chaotic neurodynamics in analog circuits

Hiroyasu Ando, Aki Nakano, Yoshihiko Horio, Kazuyuki Aihara

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

2 Citations (Scopus)

Abstract

We propose a control strategy of chaotic dynamics to stabilize periodic orbits in nonlinear discrete-time dynamical systems (maps) and apply it to a chaotic neuron map model not only numerically but also experimentally by analog circuit implementation. The control method is based on an adaptive feedback adjustment of a control parameter of the system, which uses typical bifurcation structures of nonlinear dynamical systems. We can observe a clear fractal structure in the sets composed of controlled states with respect to different initial conditions. We also discuss possible applications of the controlled system as an analog-valued memory with high-capacity.

Original language	English
Title of host publication	2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
Pages	2621-2624
Number of pages	4
DOIs	https://doi.org/10.1109/ISCAS.2009.5118339
Publication status	Published - 2009
Event	2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009 - Taipei, Taiwan, Province of China Duration: 2009 May 24 → 2009 May 27

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)	0271-4310

Conference

Conference	2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
Country/Territory	Taiwan, Province of China
City	Taipei
Period	09/5/24 → 09/5/27

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10.1109/ISCAS.2009.5118339

Cite this

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title = "Adaptive feedback control of chaotic neurodynamics in analog circuits",

abstract = "We propose a control strategy of chaotic dynamics to stabilize periodic orbits in nonlinear discrete-time dynamical systems (maps) and apply it to a chaotic neuron map model not only numerically but also experimentally by analog circuit implementation. The control method is based on an adaptive feedback adjustment of a control parameter of the system, which uses typical bifurcation structures of nonlinear dynamical systems. We can observe a clear fractal structure in the sets composed of controlled states with respect to different initial conditions. We also discuss possible applications of the controlled system as an analog-valued memory with high-capacity.",

author = "Hiroyasu Ando and Aki Nakano and Yoshihiko Horio and Kazuyuki Aihara",

year = "2009",

doi = "10.1109/ISCAS.2009.5118339",

language = "English",

isbn = "9781424438280",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

pages = "2621--2624",

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note = "2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009 ; Conference date: 24-05-2009 Through 27-05-2009",

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Ando, H, Nakano, A, Horio, Y & Aihara, K 2009, Adaptive feedback control of chaotic neurodynamics in analog circuits. in 2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009., 5118339, Proceedings - IEEE International Symposium on Circuits and Systems, pp. 2621-2624, 2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009, Taipei, Taiwan, Province of China, 09/5/24. https://doi.org/10.1109/ISCAS.2009.5118339

Adaptive feedback control of chaotic neurodynamics in analog circuits. / Ando, Hiroyasu; Nakano, Aki; Horio, Yoshihiko et al.
2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009. 2009. p. 2621-2624 5118339 (Proceedings - IEEE International Symposium on Circuits and Systems).

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

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AU - Nakano, Aki

AU - Horio, Yoshihiko

AU - Aihara, Kazuyuki

PY - 2009

Y1 - 2009

N2 - We propose a control strategy of chaotic dynamics to stabilize periodic orbits in nonlinear discrete-time dynamical systems (maps) and apply it to a chaotic neuron map model not only numerically but also experimentally by analog circuit implementation. The control method is based on an adaptive feedback adjustment of a control parameter of the system, which uses typical bifurcation structures of nonlinear dynamical systems. We can observe a clear fractal structure in the sets composed of controlled states with respect to different initial conditions. We also discuss possible applications of the controlled system as an analog-valued memory with high-capacity.

AB - We propose a control strategy of chaotic dynamics to stabilize periodic orbits in nonlinear discrete-time dynamical systems (maps) and apply it to a chaotic neuron map model not only numerically but also experimentally by analog circuit implementation. The control method is based on an adaptive feedback adjustment of a control parameter of the system, which uses typical bifurcation structures of nonlinear dynamical systems. We can observe a clear fractal structure in the sets composed of controlled states with respect to different initial conditions. We also discuss possible applications of the controlled system as an analog-valued memory with high-capacity.

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T3 - Proceedings - IEEE International Symposium on Circuits and Systems

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BT - 2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009

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Y2 - 24 May 2009 through 27 May 2009

ER -

Adaptive feedback control of chaotic neurodynamics in analog circuits

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