FIR filter design via semidefinite programming and spectral factorization

We present a semidefinite programming approach to FIR filter design with arbitrary upper and lower bounds on the frequency response magnitude. It is shown that the constraints can be expressed as linear matrix inequalities (LMIs), and hence they can be easily handled by interior-point methods. Using...

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Bibliographic Details
Published inProceedings of 35th IEEE Conference on Decision and Control Vol. 1; pp. 271 - 276 vol.1
Main Authors Shao-Po Wu, Boyd, S., Vandenberghe, L.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Constraint optimization
Constraint theory
Finite impulse response filter
Fourier transforms
Frequency response
Information systems
Laboratories
Linear matrix inequalities
Linear programming
Sufficient conditions
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Summary:We present a semidefinite programming approach to FIR filter design with arbitrary upper and lower bounds on the frequency response magnitude. It is shown that the constraints can be expressed as linear matrix inequalities (LMIs), and hence they can be easily handled by interior-point methods. Using this LMI formulation, we can cast several interesting filter design problems as convex or quasi-convex optimization problems, e.g. minimizing the length of the FIR filter and computing the Chebychev approximation of a desired power spectrum or a desired frequency response magnitude on a logarithmic scale.
ISBN:9780780335905
0780335902
ISSN:0191-2216
DOI:10.1109/CDC.1996.574313