Polynomial Filters

  • I. Pitas
  • A. N. Venetsanopoulos
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 84)


In many problems of digital signal processing it is necessary to introduce nonlinear systems. For example, it is well known that in detection and estimation problems, nonlinear filters arise in the case where the Gaussian assumption is not valid or the noise is not signal independent and/or additive. In the search for optimum signal processing systems, the task is to obtain general characterization procedures for nonlinear systems that retain at least a part of the simplicity that the impulse response method has for linear filters.


Gaussian Random Variable Kernel Matrix Volterra Series Nonlinear Filter Volterra Kernel 
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 Science+Business Media New York 1990

Authors and Affiliations

  • I. Pitas
    • 1
  • A. N. Venetsanopoulos
    • 2
  1. 1.Aristotelian University of ThessalonikiGreece
  2. 2.University of TorontoCanada

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