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Design of Fast Multidimensional Filters Using Genetic Algorithms

  • Max Langer
  • Björn Svensson
  • Anders Brun
  • Mats Andersson
  • Hans Knutsson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3449)

Abstract

A method for designing fast multidimensional filters using genetic algorithms is described. The filter is decomposed into component filters where coefficients can be sparsely scattered using filter networks. Placement of coefficients in the filters is done by genetic algorithms and the resulting filters are optimized using an alternating least squares approach. The method is tested on a 2-D quadrature filter and the method yields a higher quality filter in terms of weighted distortion compared to other efficient implementations that require the same ammount of computations to apply. The resulting filter also yields lower weighted distortion than the full implementation.

Keywords

Genetic Algorithm Transfer Function Singular Value Decomposition Output Node Fourier Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Max Langer
    • 1
  • Björn Svensson
    • 1
  • Anders Brun
    • 1
  • Mats Andersson
    • 1
  • Hans Knutsson
    • 1
  1. 1.Department of Biomedical EngineeringLinköpings universitetLinköpingSweden

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