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Acoustics, Speech, and Signal Processing, IEEE International Conference on (2009)
Taipei, Taiwan
Apr. 19, 2009 to Apr. 24, 2009
ISBN: 978-1-4244-2353-8
pp: 3197-3200
Michael Cerna , Mathematics and Signal Processing Group, National Instruments Corp., Austin, TX 78759, USA
Lothar Wenzel , Mathematics and Signal Processing Group, National Instruments Corp., Austin, TX 78759, USA
Bin Wang , Mathematics and Signal Processing Group, National Instruments Corp., Austin, TX 78759, USA
Subramanian Ramamoorthy , School of Informatics, The University of Edinburgh, EH8 9AB, UK
James Nagle , Mathematics and Signal Processing Group, National Instruments Corp., Austin, TX 78759, USA
ABSTRACT
This paper is concerned with the problem of computing a discrete-coefficient approximation to a digital filter. In contrast to earlier works that have approached this problem using standard combinatorial optimization tools, we take a geometric approach. We define a Riemannian manifold, arising from the difference in frequency response between the two systems of interest, on which we design efficient algorithms for sampling and approximation. This additional structure enables us to tame the computational complexity of the native combinatorial optimization problem. We illustrate the benefits of this approach with design examples involving IIR and FIR filters.
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CITATION
Michael Cerna, Lothar Wenzel, Bin Wang, Subramanian Ramamoorthy, James Nagle, "A differential geometric approach to discrete-coefficient filter design", Acoustics, Speech, and Signal Processing, IEEE International Conference on, vol. 00, no. , pp. 3197-3200, 2009, doi:10.1109/ICASSP.2009.4960304
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