CFP last date
22 April 2024
Reseach Article

FIR Approximation of GTD Filter Banks and their Multiresolution Optimality

by Aravind Illa, Elizabeth Elias
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 10
Year of Publication: 2014
Authors: Aravind Illa, Elizabeth Elias
10.5120/15241-3791

Aravind Illa, Elizabeth Elias . FIR Approximation of GTD Filter Banks and their Multiresolution Optimality. International Journal of Computer Applications. 87, 10 ( February 2014), 1-5. DOI=10.5120/15241-3791

@article{ 10.5120/15241-3791,
author = { Aravind Illa, Elizabeth Elias },
title = { FIR Approximation of GTD Filter Banks and their Multiresolution Optimality },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 10 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number10/15241-3791/ },
doi = { 10.5120/15241-3791 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:05:32.017511+05:30
%A Aravind Illa
%A Elizabeth Elias
%T FIR Approximation of GTD Filter Banks and their Multiresolution Optimality
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 10
%P 1-5
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The theory and design of signal adapted filter banks in the coding gain objective as well as the multiresolution objective are of great interest in many signal processing applications. The role of the generalized triangular decomposition (GTD) filter banks in optimizing perfect reconstruction filter banks has been proposed recently by Ching-Chih Weng et al. They have proposed the GTD filter bank as a subband coder for optimizing the theoretical coding gain. In this paper, we show that the design of the GTD filter bank via the singular value decomposition (SVD) will be reduced to the principal component filter bank (PCFB) and it gives optimal performance in the multiresolution objective. The FIR approximation of the optimal GTD filter banks is also discussed in this paper. This is done by using the iterative greedy algorithm.

References
  1. C. C. Weng, and P. P. Vaidyanathan, "The Role of GTD in Optimizing Perfect Reconstruction Filter Banks," IEEE Trans. Signal Process. , vol. 60, pp. 112118, Jan. 2012.
  2. S. Akkarakaran and P. P. Vaidyanathan,"Filterbank optimization with convex objectives and the optimality of principal component forms," IEEE Trans. Signal Process. , vol. 49, no. 1, pp. 100114, Jan. 2001.
  3. Sheeba V S, Elizabeth Elias, "Design of Two-Dimensional Signal Adapted Filter Banks for Application in Image Processing," WSEAS Transactions on Signal Processing Issue 9, Vol. 2, Sept. 2006, pp 1281-1286.
  4. Elizabeth Elias, Sheeba V S, and Anand R, "FIR Principal Component Filter Banks in Echo Cancellation," CSI Journal, Young Horizon-Computing and Informatics, Vol. 1, No. 1, Nov. 2006, pp 28-31.
  5. C. C. Weng, C. Y. Chen, and P. P. Vaidyanathan,"Generalized triangular decomposition in transform coding," IEEE Trans. Signal Process. , vol. 58, no. 2, pp. 566574, Feb. 2010.
  6. P. P. Vaidyanathan,"Theory of optimal orthonormal subband coders," IEEE Trans. Signal Process. , vol. 46, pp. 15281543, Jun. 1998.
  7. P. P. Vaidyanathan,"Theory of optimal orthonormal subband coders," IEEE Trans. Signal Process. , vol. 46, pp. 15281543, Jun. 1998.
  8. A. Tkacenko and P. P. Vaidyanathan, "Iterative greedy algorithm for solving the FIR paraunitary approximation problem," IEEE Trans. Signal Process. , vol. 54, pp. 146160, Jan. 2006.
  9. Y. Jiang, W. W. Hager, and J. Li, "Generalized triangular decomposition," Math. Computat. , Oct. 2007.
  10. S. M. Phoong and Y. P. Lin, "MINLAB: Minimum noise structure forladder-based biorthogonal filter banks," IEEE Trans. Signal Process. , vol. 48, no. 2, pp. 465476, Feb. 2000.
  11. S. M. Phoong and Y. P. Lin, "Prediction-based lower triangular transform," IEEE Trans. Signal Process. , vol. 48, no. 7, pp. 19471955, Jul. 2000.
  12. M. K. Tsatsanis and G. B. Giannakis,"Principal component filter banks for optimal multiresolution analysis," IEEE Trans. Signal Process. , vol. 43, no. 8, pp. 17661777, Aug. 1995.
  13. P. P. Vaidyanathan, Systems and Filter Banks. Prentice-Hall, 1993.
  14. A. Tkacenko. Matlab m-Files. [Online]. Available: http://www. systems. caltech. edu/dsp/students/andre/index. html
Index Terms

Computer Science
Information Sciences

Keywords

Generalized triangular decoposition pricipal component filter banks iterative greedy algorithm subband coder multiresolution objective singular value decomposition.