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  • 标题:On-line Approach for Fast Convolution over Sensor Networks
  • 本地全文:下载
  • 作者:Dalius Navakauskas ; Rimantas Pupeikis
  • 期刊名称:TEM Journal
  • 印刷版ISSN:2217-8309
  • 电子版ISSN:2217-8333
  • 出版年度:2018
  • 卷号:7
  • 期号:2
  • 页码:243-249
  • DOI:10.18421/TEM72-01
  • 语种:English
  • 出版社:UIKTEN
  • 摘要:It is assumed that at some time moment, in wireless sensor networks the new set of current samples of input and system impulse response enter a digital memory replacing the previous samples. It is urgent for each new sample or for a small part of new samples to update a convolution as well. Therefore,a recursive fast convolution algorithm is proposed here to solve a linear filtering problem for a nonstationary system. The calculation operations are reduced because most columns of Fourier code matrices and respective rows of the right-hand side vectors were deleted for equal previous and current samples. An example with the ordinary and modified 8-point Fourier code matrices is presented for a nonstationary linear system. The amounts of operations,necessary for recursive and fast Fourier transform algorithms,are calculated. Results are discussed,and the conclusion is given.
  • 关键词:system;response;signal;convolution;filtering.
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