The Design of Nonrecursive Digital Filters via Convex Optimization

  • Alexander W. Potchinkov
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 25)


The advantages of optimization in filter design over strongly specialized methods based upon approximation theory are well known since some years, first of all in the area of constrained linear-phase filter design. Mainly finite linear optimization has been used which requires the discretization w.r.t. the frequency variable and, if necessary, the linearization of important nonlinear filter characteristics. The work here is founded on convex finite and semi-infinite optimization. The approach avoids the discretization step and thereby, in particular, enables the design of large filters on personal computers. Moreover, convex functions such as the magnitude response, magnitude of the complex approximation error, and some quadratic error functions can be used in their original form.


Digital Filter Filter Design Magnitude Response Tolerance Scheme Reconstruction Filter 
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 Dordrecht 1998

Authors and Affiliations

  • Alexander W. Potchinkov
    • 1
  1. 1.Fakultät 1Brandenburgische Technische Universität CottbusCottbusGermany

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