{"title":"具有参数耦合映射网络的多状态联想记忆","authors":"G. Tanaka, K. Aihara","doi":"10.1142/S0218127405012673","DOIUrl":null,"url":null,"abstract":"The present paper proposes two types of multistate associative memory models using circle maps coupled through a parameter in the individual map. Each network utilizes a circle map with a specific bifurcation property as its component and realizes self-organizing chaotic dynamics in a memory association. The performance of the proposed networks is compared with that of a conventional multistate neural network in multistate associative memory tests.","PeriodicalId":426683,"journal":{"name":"The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, 2004. Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Multistate associative memory with parametrically coupled map networks\",\"authors\":\"G. Tanaka, K. Aihara\",\"doi\":\"10.1142/S0218127405012673\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present paper proposes two types of multistate associative memory models using circle maps coupled through a parameter in the individual map. Each network utilizes a circle map with a specific bifurcation property as its component and realizes self-organizing chaotic dynamics in a memory association. The performance of the proposed networks is compared with that of a conventional multistate neural network in multistate associative memory tests.\",\"PeriodicalId\":426683,\"journal\":{\"name\":\"The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, 2004. Proceedings.\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, 2004. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/S0218127405012673\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/S0218127405012673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multistate associative memory with parametrically coupled map networks
The present paper proposes two types of multistate associative memory models using circle maps coupled through a parameter in the individual map. Each network utilizes a circle map with a specific bifurcation property as its component and realizes self-organizing chaotic dynamics in a memory association. The performance of the proposed networks is compared with that of a conventional multistate neural network in multistate associative memory tests.