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  1. IEEE Signal Processing Magazine
  2. Year : 1992 Volume : 9
  3. Issue 1
  4. Frequency-domain and multirate adaptive filtering
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Issue 4
Issue 3
Issue 2
Issue 1
How the FFT gained acceptance
Frequency-domain and multirate adaptive filtering
The tensor product: a mathematical programming language for FFTs and other fast DSP operations
Year : 1991 Volume : 8

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Frequency-domain and multirate adaptive filtering

Content Provider IEEE Xplore Digital Library
Author Shynk, J.J.
Copyright Year 1991
Abstract An overview is presented of several frequency-domain adaptive filters that efficiently process discrete-time signals using block and multirate filtering techniques. These algorithms implement a linear convolution that is equivalent to a block time-domain adaptive filter, or they generate a circular convolution that is an approximation. Both approaches exploit the computational advantages of the FFT. Subband adaptive filtering is also briefly described. Here the input data are first processed by a bank of narrowband bandpass filters that are approximately nonoverlapping. The transformed signals are then decimated by a factor that depends on the degree of aliasing that can be tolerated, resulting in a large computational savings. Several performance issues are considered, including convergence properties and computational complexities of the adaptive algorithms and the effects of circular convolution and aliasing on the converged filter coefficients.<>
Starting Page 14
Ending Page 37
Page Count 24
File Size 1899460
File Format PDF
ISSN 10535888
Volume Number 9
Issue Number 1
Language English
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date 1992-01-01
Publisher Place U.S.A.
Access Restriction Subscribed
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword Adaptive filters Convolution Signal processing Filtering Approximation algorithms Time domain analysis Narrowband Band pass filters Convergence Computational complexity
Content Type Text
Resource Type Article
Subject Electrical and Electronic Engineering Applied Mathematics Signal Processing
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