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Filter Design Problems with Convex Optimization

by Sachin Rastogi, Sanjeev Rajan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 28
Year of Publication: 2018
Authors: Sachin Rastogi, Sanjeev Rajan
10.5120/ijca2018916544

Sachin Rastogi, Sanjeev Rajan . Filter Design Problems with Convex Optimization. International Journal of Computer Applications. 180, 28 ( Mar 2018), 35-40. DOI=10.5120/ijca2018916544

@article{ 10.5120/ijca2018916544,
author = { Sachin Rastogi, Sanjeev Rajan },
title = { Filter Design Problems with Convex Optimization },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2018 },
volume = { 180 },
number = { 28 },
month = { Mar },
year = { 2018 },
issn = { 0975-8887 },
pages = { 35-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number28/29156-2018916544/ },
doi = { 10.5120/ijca2018916544 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:02:05.516127+05:30
%A Sachin Rastogi
%A Sanjeev Rajan
%T Filter Design Problems with Convex Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 28
%P 35-40
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we consider the design of FIR filters that satisfy magnitude specifications. We refer to such design problems as magnitude filter design problems. In this paper it is shown that by a change of variables, a wide variety of magnitude filter design problems can be posed as convex optimization problems, i.e., problems in which the objective and constraint functions are convex.

References
  1. F.A.Aliyev, B.A. Bordyug, and V.B. Larin Factorization of polynomial matrices and separation of rational matrries. Soviet Journal of Computer and Systems Sciences, 28(6):47-58,1990.
  2. F.A. Aliyev, B.A. Bordyug, and V.B. Larin Discreate generalized algebraic Riccati equations and polynomial matrix factorization. Syst. Control Letters, 18:49-59,1992.
  3. B.Anderson. An algebraic solution to the spectral factorization problem. IEEE Trans. Aut. Contral, Ac-12(4):410-414, Aug.1967.
  4. B.Anderson. Anderson and J.B. Moore. Optimal Filtering. Prentice-Hall, 1979.
  5. B.Anderson and S.Vongpanitlerd. Network analysis and synthesis modern system theory approch. Pretice-Hall,1973.
  6. B.D.O. Anderson and K.L.Hitz, and N.D. Diem. Recursive algorithm for spectral factorization. IEEE Transactions on Circuits and System 21:742-75,1974
  7. E.J.Anderson, and P.Nash. Linear Progamming in Infinite- Dimensional Spaces.: Theory and Application John Wiley & Sons, 1987.
  8. E.J.Anderson and A.B. Philpott, editors. Infinite Programming. Springer-Verlag Lecture Notes in Economics and MathematicalSystems, Sept.1984.
  9. Y. Nesterov and A. Nemirovskii, Interior Point Polynomial Methods in Convex Programming. Philadelphia, Philadelphia: SIAM, 1994, vol. 13, Studies in AppliedMathematics.
  10. A. S. Nemirovski and M. J. Todd, “Interior-point methods for optimization,” Acta Numerica, vol. 17, pp. 191-234, May 2008.
Index Terms

Computer Science
Information Sciences

Keywords

finite-duration impulse response (FIR) convex optimization filter design spectral factorization.

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