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Multidimensional FIR Filter Design Via Trigonometric Sum-of-Squares Optimization

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3 Author(s)
Tae Roh ; California Univ., Los Angeles ; Bogdan Dumitrescu ; Lieven Vandenberghe

We discuss a method for multidimensional FIR filter design via sum-of-squares formulations of spectral mask constraints. The sum-of-squares optimization problem is expressed as a semidefinite program with low-rank structure, by sampling the constraints using discrete cosine and sine transforms. The resulting semidefinite program is then solved by a customized primal-dual interior-point method that exploits low-rank structure. This leads to a substantial reduction in the computational complexity, compared to general-purpose semidefinite programming methods that exploit sparsity.

Published in:

IEEE Journal of Selected Topics in Signal Processing  (Volume:1 ,  Issue: 4 )