{"title":"A new approach to the design of Hopfield associative memory","authors":"J. Hao, S. Tan, J. Vandewalle","doi":"10.1109/IJCNN.1991.170666","DOIUrl":null,"url":null,"abstract":"The authors present a novel method for constructing the weight matrix for the Hopfield associative memory. The most important feature of this method is the explicit introduction of the size of the attraction basin to be a main design parameter, and the weight matrix is obtained as a result of optimizing this parameter. Another feature is that all the connection weights can only assume three different values, -1, +1, and 0, which facilitates the VLSI implementation of the weights. Compared to the widely used Hebbian rule, the method can guarantee all the given patterns to be stored at least as fixed points, regardless of the internal structure of the patterns. The proposed design method is illustrated by a few examples.<<ETX>>","PeriodicalId":211135,"journal":{"name":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1991.170666","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The authors present a novel method for constructing the weight matrix for the Hopfield associative memory. The most important feature of this method is the explicit introduction of the size of the attraction basin to be a main design parameter, and the weight matrix is obtained as a result of optimizing this parameter. Another feature is that all the connection weights can only assume three different values, -1, +1, and 0, which facilitates the VLSI implementation of the weights. Compared to the widely used Hebbian rule, the method can guarantee all the given patterns to be stored at least as fixed points, regardless of the internal structure of the patterns. The proposed design method is illustrated by a few examples.<>