{"title":"在种群代码中优化优选刺激的分布","authors":"S. Wu, H. Nakahara","doi":"10.1109/ICONIP.1999.844008","DOIUrl":null,"url":null,"abstract":"We consider two methods to optimize the distribution of preferred stimulus in a population code based on the knowledge of the distribution of stimulus. One method is to maximize the mean Fisher information of the population with respect to the stimulus ensemble. The other is to minimize the lower bound of the mean decoding error. The implication of the two methods is discussed.","PeriodicalId":237855,"journal":{"name":"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimize the distribution of preferred stimulus in a population code\",\"authors\":\"S. Wu, H. Nakahara\",\"doi\":\"10.1109/ICONIP.1999.844008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider two methods to optimize the distribution of preferred stimulus in a population code based on the knowledge of the distribution of stimulus. One method is to maximize the mean Fisher information of the population with respect to the stimulus ensemble. The other is to minimize the lower bound of the mean decoding error. The implication of the two methods is discussed.\",\"PeriodicalId\":237855,\"journal\":{\"name\":\"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICONIP.1999.844008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONIP.1999.844008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimize the distribution of preferred stimulus in a population code
We consider two methods to optimize the distribution of preferred stimulus in a population code based on the knowledge of the distribution of stimulus. One method is to maximize the mean Fisher information of the population with respect to the stimulus ensemble. The other is to minimize the lower bound of the mean decoding error. The implication of the two methods is discussed.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
