International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.5, No.4, Apr. 2013

Modified Sparseness Controlled IPNLMS Algorithm Based on l_1, l_2 and l_∞ Norms

Full Text (PDF, 1707KB), PP.18-29

Views:122   Downloads:3


Krishna Samalla,Ch. Satyanarayana

Index Terms

Acoustic Echo Cancellation (AEC), Modified Sparseness Controlled Improved Proportionate Normalized Least Mean Square (MSC-IPNLMS), Sparseness Controlled Improved Proportionate Normalized Lease Mean Square (SC-IPNLMS), Sparseness measure


In the context of Acoustic Echo Cancellation (AEC), sparseness level of acoustic impulse response (AIR) varies greatly in mobile environments. The modified sparseness-controlled Improved PNLMS (MSC-IPNLMS) algorithm proposed in this paper, exploits the sparseness measure of AIR using l1, l2 and l∞ norms. The MSC-IPNLMS is the modified version of SC-IPNLMS which uses sparseness measure based on l1 and l2 norms. Sparseness measure using l1, l2 and l∞ norms is the good representation of both sparse and dense impulse response, where as the measure which uses l1 and l2 norms is the good representation of sparse impulse response only. The MSC-IPNLMS is based on IPNLMS which allocates adaptation step size gain in proportion to the magnitude of estimated filter weights. By estimating the sparseness of the AIR, the proposed MSC-IPNLMS algorithm assigns the gains for each step size such that the proportionate term of the IPNLMS will be given higher weighting for sparse impulse responses. For a less sparse impulse response, a higher weighting will be given to the NLMS term. Simulation results, with input as white Gaussian noise (WGN), show the improved performance over the SC-IPNLMS algorithm in both sparse and dense AIR.

Cite This Paper

Krishna Samalla,Ch.Satyanarayana,"Modified Sparseness Controlled IPNLMS Algorithm Based on l_1, l_2 and l_∞ Norms", IJIGSP, vol.5, no.4, pp.18-29, 2013.DOI: 10.5815/ijigsp.2013.04.03


[1]J. Radecki, Z. Zilic, and K. Radecka, "Echo cancellation in IPnetworks," in Proceedings of the 45th Midwest Symposium oCircuits and Systems, vol. 2, pp. 219–222, Tulsa, Okla, USA,August 2002.

[2]R. H. Kwong and E. Johston, "A variable step-size algorithm for adaptivefiltering," IEEE Trans. Signal processing, vol. 40, pp. 1633–1642, 1992.

[3]C. Rusu and F. N. Cowan, "The convex variable step size (CVSS) algorithm," IEEE Signal processing Letter, vol. 7, pp. 256–258, 2000.

[4]J. Sanubari, "A new variable step size method for the LMS adaptive filter," in IEEE Asia-Pacific Conference on Circuits and systems, 2004.

[5]A.W. H. Khong and P. A. Naylor, "Selective-tap adaptive algorithms in the solution of the non-uniqueness problem for stereophonic acousticecho cancellation," IEEE Signal Processing Lett., vol. 12, no. 4, pp.269–272, Apr. 2005.

[6]P. A. Naylor and A. W. H. Khong, "Affine projection and recursive least squares adaptive filters employing partial updates," in Proc. Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, vol. 1,Nov. 2004, pp. 950–954.

[7]K. A. Lee and S. Gan, "Improving convergence of the NLMS algorithm using constrained subbands updates," IEEE Signal Processing Lett.,vol. 11, no. 9, pp. 736–739, Sept. 2004.

[8]D. L. Duttweiler, "Proportionate normalized least mean square adaptation in echo cancellers," IEEE Trans. Speech Audio Processing, vol. 8,no. 5, pp. 508–518, Sep. 2000.

[9]M. M. Sondhi, "An adaptive echo canceller," Bell Syst.Tech. J., vol. XLVI-3, pp. 497–510, Mar. 1967

[10]J. Benesty, T. Gänsler, D. R. Morgan, M. M. Sondhi, and S. L. Gay, Advances in Network and Acoustic Echo Cancellation. Berlin, Germany: Springer-Verlag, 2001

[11]S. Haykin, Adaptive Filter Theory. Fourth Edition, Upper Saddle River, NJ: Prentice-Hall,2002.

[12]K.Ozeki and T. Umeda, "An adaptive filtering algorithm using an orthogonal projection to an affine subspace and its properties," Electron. Commun. Jpn., vol. 67-A, pp. 19–27, May 1984.

[13]S. L. Gay and S.Tavathia, "The fast affine projection algorithm," in Proc. IEEE ICASSP, 1995, vol. 5, pp. 3023–3026.

[14]M. Tanaka, Y. Kaneda, S. Makino, and J. Kojima, "A fast projection algorithm for adaptive filtering," IEICE Trans. Fundamentals, vol. E78-A, pp. 1355–1361, Oct. 1995.

[15]Sparse Adaptive Filters for Echo Cancellation Constantin Paleologu, Jacob Benesty, and Silviu Ciochin˘a 2010.

[16]J. Homer, I. Mareels, R. R. Bitmead, B. Wahlberg, and A. Gustafsson, "LMS estimation via structural detection," IEEE Trans. Signal Processing, vol. 46, pp. 2651–2663, Oct. 1998.

[17]S. Makino, Y. Kaneda, and N. Koizumi, "Exponentially weighted step-size NLMS adaptive filter based on the statistics of a room impulse response," IEEE Trans. Speech, Audio Processing.

[18]A. Sugiyama, H. Sato,A. Hirano, and S. Ikeda, "A fast convergence algorithm for adaptive FIR filters under computational constraint for adaptive tap-position control," IEEE Trans. Circuits Syst. II, vol. 43, pp. 629–636, Sept. 1996.

[19]D. L.Duttweiler, "Proportionate normalized least-mean-squares adaptation in echo cancelers," IEEETrans. Speech,Audio Processing, vol. 8, pp. 508–518, Sept. 2000.

[20]J. Benesty and S. L. Gay, "An improved PNLMS algorithm," in Proc. IEEE ICASSP, 2002, pp.1881–1884

[21]J. Kivinen and M. K. Warmuth, "Exponentiated gradient versus gradient descent for linearpredictors," Inform. Comput., vol. 132, pp. 1–64, Jan. 1997.

[22]H. Deng and M. Doroslovaˇcki, "Improving convergence of the PNLMS algorithm for sparse impulse response identification," IEEE Signal Processing Lett., vol. 12, pp. 181–184, Mar. 2005.

[23]H. Deng and M. Doroslovaˇcki, "Proportionate adaptive algorithms for network echo cancellation," IEEE Trans. Signal Processing, vol. 54, pp. 1794–1803, May 2006..

[24]A new variable step size lms adaptive filtering Algorithm, AO Wei, XIANG Wan-Qin, ZHANG You-Peng, WANG Lei, 978-0-7695-4647-6/12 © 2012 IEEE DOI 10.1109/ICCSEE.2012.115

[25]K. Dogancay and P. A. Naylor, "Recent advances in partial update and sparsea daptive filters," in Proc. European Signal Processing Conference, 2005

[26]S. Makino, Y. Kaneda, and N. Koizumi, "Exponentially weighted step-size NLMS adaptive filter based on the statistics of a room impulse response," IEEE Trans. Speech, Audio Processing, vol. 1, pp. 101–108, Jan. 1993

[27]Krishna Samalla,Dr.Ch Satyanarayana"Survey of Sparse Adaptive Filters for Acoustic Echo Cancellation" I.J. Image, Graphics and Signal Processing, 2013, 1, 16-24 Published Online January 2013 in MECS ( DOI: 10.5815/ijigsp.2013.1.03