Efficient Cosine Modulated Filter Bank using Multiplierless Masking Filter and Representation of Prototype Filter Coefficients Using CSD

Full Text (PDF, 1613KB), PP.25-33

Views: 0 Downloads: 0

Author(s)

Supriya Dhabal 1,* Palaniandavar Venkateswaran 2

1. Netaji Subhash Engineering College Kolkata, West Bengal, India

2. Jadavpur University, Kolkata, West Bengal, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2012.10.04

Received: 16 May 2012 / Revised: 11 Jul. 2012 / Accepted: 17 Aug. 2012 / Published: 28 Sep. 2012

Index Terms

IFIR, SLFOR, CSD, Optimization

Abstract

This paper presents a design of low complexity multichannel Nearly Perfect Reconstruction (NPR) Cosine Modulated Filter Bank (CMFB). CMFBs are used extensively because of ease realization and the inherent advantage of high stop-band attenuation. But, when the number of channel becomes large, it leads to certain limitations as it would require large number of filter coefficients to be optimized and hence longer CPU time; e.g. 32-band or 64-band CMFB. Large number of filter coefficients would also mean that computational complexity of the prototype filter is extremely increased that tends to slow down the convergence to best possible solution. Here, the prototype filter is designed using modified Interpolated Finite Impulse Response (IFIR) technique where masking filter is replaced by multiplier free cascaded structure and coefficients of model filter are converted to nearest Canonical Signed Digit (CSD). The interpolation factor is chosen in such a way that computational cost of the overall filter and different error parameters are reduced. The proposed approach thus leads to reduction in stop-band energy as well as high Side-Lobe-Fall-off-Rate (SLFOR). Three examples have been included to demonstrate the effectiveness of the proposed technique over the existing design methods and savings in computational complexity is also highlighted.

Cite This Paper

Supriya Dhabal,Palaniandavar Venkateswaran,"Efficient Cosine Modulated Filter Bank Using Multiplierless Masking Filter and Representation of Prototype Filter Coefficients Using CSD", IJIGSP, vol.4, no.10, pp.25-33, 2012. DOI: 10.5815/ijigsp.2012.10.04

Reference

[1]J. D. Johnston, “A filter family designed for use in quadrature mirror filter banks”, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, 1980, pp. 291-294.

[2]C.D. Creusere and S.K. Mitra, “A Simple method for designing high quality prototype filters for M-band pseudo QMF banks”, IEEE Trans. on Signal Processing, Vol 43, pp.1005-1007, April 1994.

[3]Troung Q, Nguyen, “Near-perfect-reconstruction pseudo-QMF banks”, IEEE Trans. on Signal Processing, Vol. 42, no. 1, pp. 65-76, 1994.

[4]M. B. Furado, P. Diniz, S. L. Netto and T. Saramaki, “On the Design of High-Complexity Cosine-Modulated Trans-multiplexers Based on the Frequency-Response Masking Approach,” IEEE Trans. on Circuits and System, Vol. 52, No. 11, Nov. 2005, pp. 2413-2426.

[5]Felicja W. Schillak, “Design of Low-Delay Cosine-Modulated Filter Banks with Equiripple Reconstruction Error”, International Conference on Signals and Electronics Systems, Sept. 14-17, 2008. 

[6]Dhabal S, Chowdhury S.M.L, Venkateswaran P. , "A novel low complexity multichannel Cosine Modulated Filter Bank using IFIR technique for Nearly Perfect Reconstruction," Recent Advances in Information Technology (RAIT), pp.208-213, 15-17 March 2012

[7]R. Bregovic and T. Saramaki, “An efficient approach for designing nearly perfect-reconstruction low-delay cosine-modulated filter banks”, IEEE ISCAS, May 2002, vol. 1, pp. I–825–I–828.

[8]W. S. Lu, T. Saramaki, and R. Bregovic, “Design of practically perfect- reconstruction cosine modulated filter banks: A second-order cone programming approach”, IEEE Trans. Circuits Syst., Reg. Papers, vol. 51, no. 3, pp. 552–563, Mar. 2004.

[9]A. Kumar, G.K.Singh, R.S.Anand, “A simple design method for the cosine-modulated filter banks using weighted constrained least square technique”, Journal of the Franklin Institute, 606–621.

[10]Y. Neuvo, C. Y. Dong and S. K. Mitra, “Interpolated Finite Impulse Response Filters”, IEEE Transactions on Acoust, Speech, Signal Processing, Vol. ASSP-32, June 1984, pp. 563-570.

[11]A. Mehrnia and J. A. Willson, “On Optimal IFIR Filter Design”, IEEE Proceedings of the 2004 International Symposium on Circuits and Systems, Vol. 3, May 2004, pp. 133-136.

[12]Neela Rayavarapu, Neelam Rup Prakash, “An Efficient IFIR Filter Based Prototype Filter Design for Cosine Modulated Transmultiplexers”, 2010 International Conference on Signal Acquisition and Processing. 

[13]Yuan-pei Lin and P.P. Vaidyanathan, “A Kaiser Window approach for the design of prototype filters of cosine modulated filter banks”, IEEE Signal Processing Letters, vol5, pp.132-134, June 1998.

[14]R.K.Soni, A. Jain, R. Saxena, ”Design of M-Band NPR Cosine- Modulated Filter bank Using IFIR Technique”, Journal of Signal and Information Processing, 2010, 35-43.

[15]R.M.Hewlitt and E.S. Swartzlantler, “Canonical signed digit representation for FIR digital filters”, in Proc. IEEE Workshop on Signal Processing Systems (SiPS 2000), pp. 416-426, 2000.

[16]F. Cruz-Roldan,, P. A. López, S. M. Bascón and Stuart S. Lawson, “An Efficient and Simple Method for Designing Prototype Filters for Cosine-Modulated Pseudo-QMF Banks”, IEEE Signal Processing Letters, vol.9, no.1, Jan 2002, pp. 29-31. 

[17]P. Vaidyanathan, Multirate Systems and Filter Banks. Englewood Cliffs, NJ: Prentice-Hall, 1993. 

[18]H. H. Kha, H. D. Tuan and T. Q. Nguyen, “Efficient Design of Cosine-Modulated Filter banks via Convex Optimization” IEEE Trans. on Signal Processing, Vol.57, No. 3, Mar. 2009, pp. 966-976.