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

被引：14

作者：

Roh, Tae ^{[1
]}

Dumitrescu, Bogdan ^{[2
]}

Vandenberghe, Lieven ^{[1
]}

机构：

[1] Univ So Calif, Dept Elect Engn, Los Angeles, CA 90089 USA

[2] Tampere Univ Technol, Tampere Int Ctr Signal Proc, FIN-33101 Tampere, Finland

来源：

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING | 2007年 / 1卷 / 04期

基金：

芬兰科学院;

关键词：

Discrete transforms; multidimensional digital filters; optimization methods; semidefinite programming; sum-of-squares relaxation;

D O I：

10.1109/JSTSP.2007.910261

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：641 / 650

页数：10

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