{"title":"基于离散小波变换的神经接口信号处理","authors":"J. Lee, D. Kipke","doi":"10.1109/MMB.2006.251519","DOIUrl":null,"url":null,"abstract":"This paper presents a neural signal processing ASIC based on discrete wavelet transform (DWT). The recorded neural signals from 256 channels are analyzed by fast DWT algorithm with special ALUs, then, compressed by run-length encoders (RLE). The processed data are delivered through RF links and reconstructed in a host receiver. This design operates at 200 MHz clock with 2.5 V and was implemented with TSMC 0.25 mum technology. Recorded neural data test shows 1:89:3 (1.12%) compression rate and perfect in-band noise rejection","PeriodicalId":170356,"journal":{"name":"2006 International Conference on Microtechnologies in Medicine and Biology","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Neural Signal Processing using Discrete Wavelet Transform for Neural Interfaces\",\"authors\":\"J. Lee, D. Kipke\",\"doi\":\"10.1109/MMB.2006.251519\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a neural signal processing ASIC based on discrete wavelet transform (DWT). The recorded neural signals from 256 channels are analyzed by fast DWT algorithm with special ALUs, then, compressed by run-length encoders (RLE). The processed data are delivered through RF links and reconstructed in a host receiver. This design operates at 200 MHz clock with 2.5 V and was implemented with TSMC 0.25 mum technology. Recorded neural data test shows 1:89:3 (1.12%) compression rate and perfect in-band noise rejection\",\"PeriodicalId\":170356,\"journal\":{\"name\":\"2006 International Conference on Microtechnologies in Medicine and Biology\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Microtechnologies in Medicine and Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMB.2006.251519\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Microtechnologies in Medicine and Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMB.2006.251519","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural Signal Processing using Discrete Wavelet Transform for Neural Interfaces
This paper presents a neural signal processing ASIC based on discrete wavelet transform (DWT). The recorded neural signals from 256 channels are analyzed by fast DWT algorithm with special ALUs, then, compressed by run-length encoders (RLE). The processed data are delivered through RF links and reconstructed in a host receiver. This design operates at 200 MHz clock with 2.5 V and was implemented with TSMC 0.25 mum technology. Recorded neural data test shows 1:89:3 (1.12%) compression rate and perfect in-band noise rejection
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