The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 1990년 Pecora와 Carroll이 제안한 기존 방법과 달리 시스템 연결이 필요하지 않은 카오스 시스템 동기화를 위한 제어 방법을 제안한다. 이 방법은 강화학습 알고리즘을 기반으로 한다. 우리는 매개변수가 일치하지 않는 두 개의 이산시간 혼돈 시스템에 우리 방법을 적용하고 다음을 달성합니다. M 단계 지연 동기화. 또한 제안된 방법을 연속시간 카오스 시스템의 동기화로 확장합니다.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
부
Norihisa SATO, Masaharu ADACHI, "Synchronization of Chaotic Systems without Direct Connections Using Reinforcement Learning" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 4, pp. 958-965, April 2009, doi: 10.1587/transfun.E92.A.958.
Abstract: In this paper, we propose a control method for the synchronization of chaotic systems that does not require the systems to be connected, unlike existing methods such as that proposed by Pecora and Carroll in 1990. The method is based on the reinforcement learning algorithm. We apply our method to two discrete-time chaotic systems with mismatched parameters and achieve M step delay synchronization. Moreover, we extend the proposed method to the synchronization of continuous-time chaotic systems.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.958/_p
부
@ARTICLE{e92-a_4_958,
author={Norihisa SATO, Masaharu ADACHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Synchronization of Chaotic Systems without Direct Connections Using Reinforcement Learning},
year={2009},
volume={E92-A},
number={4},
pages={958-965},
abstract={In this paper, we propose a control method for the synchronization of chaotic systems that does not require the systems to be connected, unlike existing methods such as that proposed by Pecora and Carroll in 1990. The method is based on the reinforcement learning algorithm. We apply our method to two discrete-time chaotic systems with mismatched parameters and achieve M step delay synchronization. Moreover, we extend the proposed method to the synchronization of continuous-time chaotic systems.},
keywords={},
doi={10.1587/transfun.E92.A.958},
ISSN={1745-1337},
month={April},}
부
TY - JOUR
TI - Synchronization of Chaotic Systems without Direct Connections Using Reinforcement Learning
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 958
EP - 965
AU - Norihisa SATO
AU - Masaharu ADACHI
PY - 2009
DO - 10.1587/transfun.E92.A.958
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2009
AB - In this paper, we propose a control method for the synchronization of chaotic systems that does not require the systems to be connected, unlike existing methods such as that proposed by Pecora and Carroll in 1990. The method is based on the reinforcement learning algorithm. We apply our method to two discrete-time chaotic systems with mismatched parameters and achieve M step delay synchronization. Moreover, we extend the proposed method to the synchronization of continuous-time chaotic systems.
ER -