{"title":"尖峰神经网络中的噪声形成-网络设计问题","authors":"C. Mayr, R. Schuffny","doi":"10.1109/MWSCAS.2004.1354178","DOIUrl":null,"url":null,"abstract":"In recent years, there has been an increased focus on the mechanics of information transmission in spiking neural networks. Especially the noise shaping properties of these networks and their similarity to delta-sigma modulators has received a lot of attention. However, very little of the research done in this area has focused on the effect the weights in these networks have on the noise shaping properties. This paper concerns itself with the various modes of network operation and beneficial as well as detrimental effects which the systematic generation of network weights can effect. Relevancy of this research to industrial application of neural nets as building blocks of oversampled A/D converters is shown. Also, further points of contention are listed, which must be thoroughly researched to add to the above mentioned applicability of spiking neural nets.","PeriodicalId":185817,"journal":{"name":"The 2004 47th Midwest Symposium on Circuits and Systems, 2004. MWSCAS '04.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Noise shaping in spiking neural nets - network design issues\",\"authors\":\"C. Mayr, R. Schuffny\",\"doi\":\"10.1109/MWSCAS.2004.1354178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, there has been an increased focus on the mechanics of information transmission in spiking neural networks. Especially the noise shaping properties of these networks and their similarity to delta-sigma modulators has received a lot of attention. However, very little of the research done in this area has focused on the effect the weights in these networks have on the noise shaping properties. This paper concerns itself with the various modes of network operation and beneficial as well as detrimental effects which the systematic generation of network weights can effect. Relevancy of this research to industrial application of neural nets as building blocks of oversampled A/D converters is shown. Also, further points of contention are listed, which must be thoroughly researched to add to the above mentioned applicability of spiking neural nets.\",\"PeriodicalId\":185817,\"journal\":{\"name\":\"The 2004 47th Midwest Symposium on Circuits and Systems, 2004. MWSCAS '04.\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2004 47th Midwest Symposium on Circuits and Systems, 2004. MWSCAS '04.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MWSCAS.2004.1354178\",\"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 47th Midwest Symposium on Circuits and Systems, 2004. MWSCAS '04.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MWSCAS.2004.1354178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Noise shaping in spiking neural nets - network design issues
In recent years, there has been an increased focus on the mechanics of information transmission in spiking neural networks. Especially the noise shaping properties of these networks and their similarity to delta-sigma modulators has received a lot of attention. However, very little of the research done in this area has focused on the effect the weights in these networks have on the noise shaping properties. This paper concerns itself with the various modes of network operation and beneficial as well as detrimental effects which the systematic generation of network weights can effect. Relevancy of this research to industrial application of neural nets as building blocks of oversampled A/D converters is shown. Also, further points of contention are listed, which must be thoroughly researched to add to the above mentioned applicability of spiking neural nets.