PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A differential geometric approach to discrete-coefficient filter design
Subramanian Ramamoorthy, L. Wenzel, J. Nagle, B. Wang and M. Cerna
In: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 19 - 24 April 2009, Taiwan.

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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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:4824
Deposited By:Subramanian Ramamoorthy
Deposited On:24 March 2009