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Analysis of a Fast Quasi-Newton adaptive filtering algorithm

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Advances in Communications and Signal Processing

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 129))

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Abstract

The Fast Quasi-Newton algorithm described in this paper has been seen to avoid the performance degradation caused in basic adaptive algorithms by colored input signals. The FQN algorithm offers convergence performance far superior to LMS, and is comparable to RLS in tracking ability. At the same time, FQN requires only O(N) computation, and should prove to be robust in finite-precision implementation. The latter expectation results from the fact that the FQN algorithm has no internal variables that are recursively computed for more than N time steps. Thus round-off errors are not allowed to accumulate. The FQN algorithm should prove to be useful in a variety of adaptive system applications.

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References

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Author information

Authors and Affiliations

  1. MIT Lincoln Laboratory, USA

    Daniel F. Marshall

  2. Department of Elec. and Comp. Engr. and The Coordinated Science Laboratory, USA

    W. Kenneth Jenkins

Authors
  1. Daniel F. Marshall
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  2. W. Kenneth Jenkins
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Editor information

William A. Porter Subhash C. Kak

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© 1989 Springer-Verlag

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Marshall, D.F., Jenkins, W.K. (1989). Analysis of a Fast Quasi-Newton adaptive filtering algorithm. In: Porter, W.A., Kak, S.C. (eds) Advances in Communications and Signal Processing. Lecture Notes in Control and Information Sciences, vol 129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0042737

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  • DOI: https://doi.org/10.1007/BFb0042737

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-51424-4

  • Online ISBN: 978-3-540-46259-0

  • eBook Packages: Springer Book Archive

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