{"title":"Controlling chaos in a chaotic neutron","authors":"Xiaolin Ren, Guangrui Hu, Z. Tan","doi":"10.1109/IECON.1999.816473","DOIUrl":null,"url":null,"abstract":"In this paper, the problem of controlling chaos in a chaotic neuron is investigated. Specially, a simpler pulse feedback method is introduced, in which constant pulses are used to control chaos. The authors call this method the constant pulse feedback (CPF) method. The CPF method does not require any a priori knowledge of the dynamics of the system, such as the stable fixed points or unstable periodic orbits. The stability analysis is employed to study the nature of controlling chaos of the CPF method, and then the method is applied to control chaos in a neuron when it is in chaotic state. Both theoretical and numerical results show CPF method can stabilize the neuron state on desired fixed points or periodic orbits efficiently.","PeriodicalId":378710,"journal":{"name":"IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.1999.816473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, the problem of controlling chaos in a chaotic neuron is investigated. Specially, a simpler pulse feedback method is introduced, in which constant pulses are used to control chaos. The authors call this method the constant pulse feedback (CPF) method. The CPF method does not require any a priori knowledge of the dynamics of the system, such as the stable fixed points or unstable periodic orbits. The stability analysis is employed to study the nature of controlling chaos of the CPF method, and then the method is applied to control chaos in a neuron when it is in chaotic state. Both theoretical and numerical results show CPF method can stabilize the neuron state on desired fixed points or periodic orbits efficiently.