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  • 标题:A Review on Transform Domain Adaptive Filters
  • 本地全文:下载
  • 作者:Sangeeta Sharma ; Deepak Gupta ; V K Gupta
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2014
  • 卷号:5
  • 期号:5
  • 页码:6609-6613
  • 出版社:TechScience Publications
  • 摘要:In this paper, transform domain adaptive filters are studied and reviewed based on previous researches. In transform domain adaptive filters orthogonality properties of transformation such as discrete cosine transform (DCT), discrete sine transform (DST), wavelet transform and discrete fourier transform (DFT) are used to achieve an improved convergence rate as compared to the time domain analysis. Also, it provides better computational speed, fast convolution as compared to time domain algorithms. TDAF are applied when long memory or long durartion impulse response is required since it increases the computational complexity in time domain. A tabular format of review is also given for all transform domain adaptive filters algorithms, characteristics and their application areas.
  • 关键词:Tranform doimain adaptive filter; convergence;rate;introduction; discrete cosine transform; discrete sine;transform; Fourier Transform
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