{"title":"一种新的加权LBG神经脉冲压缩算法","authors":"Sudhir Rao, A. Paiva, J. Príncipe","doi":"10.1109/IJCNN.2007.4371245","DOIUrl":null,"url":null,"abstract":"In this paper, we present a weighted Linde-Buzo-Gray algorithm (WLBG) as a powerful and efficient technique for compressing neural spike data. We compare this technique with the recently proposed self-organizing map with dynamic learning (SOM-DL) and the traditional SOM. A significant achievement of WLBG over SOM-DL is a 15 dB increase in the SNR of the spike data apart from having a compression ratio of 150 : 1. Being simple and extremely fast, this algorithm allows real-time implementation on DSP chips opening new opportunities in BMI applications.","PeriodicalId":350091,"journal":{"name":"2007 International Joint Conference on Neural Networks","volume":"47 18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A Novel Weighted LBG Algorithm for Neural Spike Compression\",\"authors\":\"Sudhir Rao, A. Paiva, J. Príncipe\",\"doi\":\"10.1109/IJCNN.2007.4371245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a weighted Linde-Buzo-Gray algorithm (WLBG) as a powerful and efficient technique for compressing neural spike data. We compare this technique with the recently proposed self-organizing map with dynamic learning (SOM-DL) and the traditional SOM. A significant achievement of WLBG over SOM-DL is a 15 dB increase in the SNR of the spike data apart from having a compression ratio of 150 : 1. Being simple and extremely fast, this algorithm allows real-time implementation on DSP chips opening new opportunities in BMI applications.\",\"PeriodicalId\":350091,\"journal\":{\"name\":\"2007 International Joint Conference on Neural Networks\",\"volume\":\"47 18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.2007.4371245\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2007.4371245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Weighted LBG Algorithm for Neural Spike Compression
In this paper, we present a weighted Linde-Buzo-Gray algorithm (WLBG) as a powerful and efficient technique for compressing neural spike data. We compare this technique with the recently proposed self-organizing map with dynamic learning (SOM-DL) and the traditional SOM. A significant achievement of WLBG over SOM-DL is a 15 dB increase in the SNR of the spike data apart from having a compression ratio of 150 : 1. Being simple and extremely fast, this algorithm allows real-time implementation on DSP chips opening new opportunities in BMI applications.
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