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A Study on the Least Squares Reduced Parameter Approximation of FIR Digital Filters
Authors: S. Seyedtabaii, E. Seyedtabaii
Abstract:
Rounding of coefficients is a common practice in hardware implementation of digital filters. Where some coefficients are very close to zero or one, as assumed in this paper, this rounding action also leads to some computation reduction. Furthermore, if the discarded coefficient is of high order, a reduced order filter is obtained, otherwise the order does not change but computation is reduced. In this paper, the Least Squares approximation to rounded (or discarded) coefficient FIR filter is investigated. The result also succinctly extended to general type of FIR filters.Keywords: Digital filter, filter approximation, least squares, model order reduction.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084202
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[1] A. Antoniou, Digital Filters: Analysis, Design and Applications. New York:McGraw-Hill, 1993.
[2] A. Betser and E. Zeheb, "Reduced order IIR approximation to FIR digital filters," IEEE Trans. Signal Processing, Vol. 39, Nov. 1991, pp.2540-2544.
[3] B. Beliczynski, I. Kale and G. D. Cain, "Approximation of FIR by IIR digital filter: an algorithm based on balanced model reduction," IEEE Trans. Signal Processing, vol. 40, no. 3, Mar. 1992, pp.532-542.
[4] V. Sreeram and P. Agathoklis, "Design of linear-phase IIR filters via impulse-response gramians," IEEE Trans. Signal Processing, vol. 40, 1992, pp.389-394.
[5] S.C. Peng, B.S. Chen, and B.W. Chiou, "IIR filter design via optimal hankel-norm approximation," Proc. Inst. Elect. Eng., vol. 139, 1992, pp.586-590.
[6] K. Glover, "All optimal Hankel-norm approximations of linear multivariable systems and their ∞-error bounds," Int. Journal of Control, Vol.39, 1984, pp.1115-1193.
[7] L.Li, L. Xie, , W.Y. Yan, and Y. C. Soh, "Design of Low-Order Linear- Phase IIR Filters via Orthogonal Projection," IEEE Trans. . Signal Processing, vol. 47, no. 2, Feb.1999, pp448-457
[8] D. Enns, "Model reduction with balanced realizations: an error bound and a frequency weighted generalization," in: Proc. 23rd IEEE Conf. on Decision and Control, Las Vegas, 1984, pp.127-132.
[9] H. E. El-Game1, J. J. Soltis and M. Ahmadi, "Order reduction technique using the Chebyshev polynomial and its application in digital filter design," IEE Proc.- Circuits Devices Syst., Vol. 142, No. I, February 1995.