Efficient sparse FIR filter design

We consider the problem of designing a sparse FIR filter and show that it can be cast into a problem of determining a sparse solution of a linear system of equations. Previously proposed design algorithms for FIR filter utilize an intelligent search over all possible structures for sparse filter. We propose a new filter design method based on a simpler algorithm for finding a sparse solution of the linear system. Simulation experiments show significant improvements over classical nonsparse methods.

[1]  Yong Hoon Lee,et al.  Design of sparse FIR filters based on branch-and-bound algorithm , 1997, Proceedings of 40th Midwest Symposium on Circuits and Systems. Dedicated to the Memory of Professor Mac Van Valkenburg.

[2]  S. Chen,et al.  Fast orthogonal least squares algorithm for efficient subset model selection , 1995, IEEE Trans. Signal Process..

[3]  Bhaskar D. Rao,et al.  Signal processing with the sparseness constraint , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[4]  Yong Hoon Lee,et al.  Design of nonuniformly spaced linear-phase FIR filters using mixed integer linear programming , 1996, IEEE Trans. Signal Process..

[5]  Richard J. Hartnett,et al.  On the use of cyclotomic polynomial prefilters for efficient FIR filter design , 1993, IEEE Trans. Signal Process..

[6]  Simon Haykin,et al.  Simple and robust methods for support vector expansions , 1999, IEEE Trans. Neural Networks.

[7]  David C. Munson,et al.  Chebyshev optimization of sparse FIR filters using linear programming with an application to beamforming , 1996, IEEE Trans. Signal Process..

[8]  Balas K. Natarajan,et al.  Sparse Approximate Solutions to Linear Systems , 1995, SIAM J. Comput..