{"title":"A high performance continuous data flow filter using sliding discrete Fourier transform (DFT) and one point inverse DFT","authors":"Wen Zhuo, E. Micheli-Tzanakou","doi":"10.1109/ITAB.1998.674672","DOIUrl":null,"url":null,"abstract":"This paper presents a high performance frequency domain filter implementation for a moving window-type processing. The computational structure consists of three stages: a sliding discrete Fourier transform (SDFT) for a vectorized updating of the DFT; a frequency domain filter; and a one-point inverse discrete Fourier transform (IDFT). The total computation required for generating one filtered output point is 2/spl times/N multiplications (N is the frequency window length) and 3/spl times/N additions compared to 2/spl times/N/spl times/log/sub 2/N multiplications and additions if using FFT and IFFT. The proposed structure also has the advantage of being parallel in nature and can be used in various real-time frequency processing, continuous data flow, single or multiple channel applications.","PeriodicalId":126564,"journal":{"name":"Proceedings. 1998 IEEE International Conference on Information Technology Applications in Biomedicine, ITAB '98 (Cat. No.98EX188)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 1998 IEEE International Conference on Information Technology Applications in Biomedicine, ITAB '98 (Cat. No.98EX188)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITAB.1998.674672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper presents a high performance frequency domain filter implementation for a moving window-type processing. The computational structure consists of three stages: a sliding discrete Fourier transform (SDFT) for a vectorized updating of the DFT; a frequency domain filter; and a one-point inverse discrete Fourier transform (IDFT). The total computation required for generating one filtered output point is 2/spl times/N multiplications (N is the frequency window length) and 3/spl times/N additions compared to 2/spl times/N/spl times/log/sub 2/N multiplications and additions if using FFT and IFFT. The proposed structure also has the advantage of being parallel in nature and can be used in various real-time frequency processing, continuous data flow, single or multiple channel applications.