A Current-Mode Sampled-Data Chaos Circuit with Nonlinear Mapping Function Learning

Kei EGUCHI; Takahiro INOUE; Kyoko TSUKANO

A Current-Mode Sampled-Data Chaos Circuit with Nonlinear Mapping Function Learning

Kei EGUCHI, Takahiro INOUE, Kyoko TSUKANO

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A new current-mode sampled-data chaos circuit is proposed. The proposed circuit is composed of an operation block, a parameter block, and a delay block. The nonlinear mapping functions of this circuit are generated in the neuro-fuzzy based operation block. And these functions are determined by supervised learning. For the proposed circut, the dynamics of the learning and the state of the chaos are analyzed by computer simulations. The design conditions concerning the bifurcation diagram and the nonlinear mapping function are presented to clarify the chaos generating conditions and the effect of nonidealities of the proposed circuit. The simulation results showed that the nonlinear mapping functions can be realized with the precision of the order of several percent and that different kinds of bifurcation modes can be generated easily.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E80-A No.9 pp.1572-1577

Publication Date: 1997/09/25

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Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and its Applications)

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Kei EGUCHI, Takahiro INOUE, Kyoko TSUKANO, "A Current-Mode Sampled-Data Chaos Circuit with Nonlinear Mapping Function Learning" in IEICE TRANSACTIONS on Fundamentals, vol. E80-A, no. 9, pp. 1572-1577, September 1997, doi: .
Abstract: A new current-mode sampled-data chaos circuit is proposed. The proposed circuit is composed of an operation block, a parameter block, and a delay block. The nonlinear mapping functions of this circuit are generated in the neuro-fuzzy based operation block. And these functions are determined by supervised learning. For the proposed circut, the dynamics of the learning and the state of the chaos are analyzed by computer simulations. The design conditions concerning the bifurcation diagram and the nonlinear mapping function are presented to clarify the chaos generating conditions and the effect of nonidealities of the proposed circuit. The simulation results showed that the nonlinear mapping functions can be realized with the precision of the order of several percent and that different kinds of bifurcation modes can be generated easily.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e80-a_9_1572/_p

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@ARTICLE{e80-a_9_1572,
author={Kei EGUCHI, Takahiro INOUE, Kyoko TSUKANO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Current-Mode Sampled-Data Chaos Circuit with Nonlinear Mapping Function Learning},
year={1997},
volume={E80-A},
number={9},
pages={1572-1577},
abstract={A new current-mode sampled-data chaos circuit is proposed. The proposed circuit is composed of an operation block, a parameter block, and a delay block. The nonlinear mapping functions of this circuit are generated in the neuro-fuzzy based operation block. And these functions are determined by supervised learning. For the proposed circut, the dynamics of the learning and the state of the chaos are analyzed by computer simulations. The design conditions concerning the bifurcation diagram and the nonlinear mapping function are presented to clarify the chaos generating conditions and the effect of nonidealities of the proposed circuit. The simulation results showed that the nonlinear mapping functions can be realized with the precision of the order of several percent and that different kinds of bifurcation modes can be generated easily.},
keywords={},
doi={},
ISSN={},
month={September},}

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TY - JOUR
TI - A Current-Mode Sampled-Data Chaos Circuit with Nonlinear Mapping Function Learning
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1572
EP - 1577
AU - Kei EGUCHI
AU - Takahiro INOUE
AU - Kyoko TSUKANO
PY - 1997
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E80-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 1997
AB - A new current-mode sampled-data chaos circuit is proposed. The proposed circuit is composed of an operation block, a parameter block, and a delay block. The nonlinear mapping functions of this circuit are generated in the neuro-fuzzy based operation block. And these functions are determined by supervised learning. For the proposed circut, the dynamics of the learning and the state of the chaos are analyzed by computer simulations. The design conditions concerning the bifurcation diagram and the nonlinear mapping function are presented to clarify the chaos generating conditions and the effect of nonidealities of the proposed circuit. The simulation results showed that the nonlinear mapping functions can be realized with the precision of the order of several percent and that different kinds of bifurcation modes can be generated easily.
ER -