Variable Step Size LMS Algorithm Based on Two Cooperative Adaptive Filters

Qing Feng Wang; Chuan Lin

doi:10.4028/www.scientific.net/AMR.268-270.1168

Paper Titles

Temperature Software Compensation of Air Level Posture Sensor
p.1148

Reseach on Secondary Cooling Dynamic Control Model in Continuous Casting of Slabs
p.1152

Extraction of Individual Tree Height Using a Combination of Large-Scale Aerial Photo and LiDAR
p.1157

Research for Data Association of Power Dispatching Based on REST Web Services
p.1163

Variable Step Size LMS Algorithm Based on Two Cooperative Adaptive Filters
p.1168

The Research on LED Drive Technology Parameters and Testing Methods
p.1173

Simulating Analysis and Choosing Control Method on the Speed Control of Egg Quality’s Detection
p.1179

Bee Immune Evolutionary Algorithm
p.1184

Optimal Algorithm of Shuffled Frog Leaping Based on Immune Evolutionary Particle Swarm Optimization
p.1188

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 268-270Variable Step Size LMS Algorithm Based on Two...

Variable Step Size LMS Algorithm Based on Two Cooperative Adaptive Filters

Abstract:

A new variable step size LMS algorithm (CoLMS algorithm) based on two cooperative adaptive filters was proposed. In the CoLMS algorithm, the step size of each component filter was adjusted according to the comparison result of the two component filters’ performance at current stage. And the output of the better component adaptive filter was chosen as that of the overall adaptive filter. The CoLMS algorithm is not sensitive to the magnitude of the output noise and has a good tracking ability in the stationary or slowly changed environment. In order to further improve the tracking ability of CoLMS in abruptly changed environment, a modified CoLMS algorithm is also presented. The efficiency of the new algorithms is verified by the simulation results in system identification under the noises of different magnitudes.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 268-270)

Pages:

1168-1172

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.268-270.1168

Citation:

Cite this paper

Online since:

July 2011

Authors:

Qing Feng Wang, Chuan Lin

Keywords:

Adaptive Filtering, Cooperation, Least Mean Square Algorithm, Variable Step Size

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] X.D. Luo, Z.H. Jia, Q. Wang: A New Variable Step Size LMS Adaptive Filtering Algorithm. Acta Electronica Sinica, Vol. 34(2006), p.1123.

Google Scholar

[2] R.M. Lan, P.Y. Tang. New variable step-size LMS adaptive algorithm[J]. System Engineering and Electronics, Vol. 27(2005), p.1307.

Google Scholar

[3] Tyseer Aboulnasr, K. Mayyas. A Robust Variable Step-Size LMS-Tpye Algorithm: Analysis and Simulations[J]. IEEE Trans. On Signal Processing, Vol. 45(1997), p.631.

DOI: 10.1109/78.558478

Google Scholar

[4] C. Lin, Q.Y. Feng. Fuzzy Step Size LMS Algorithm and Its Performance Analysis[J]. System Engineering and Electronics, 29(2007), p.967.

Google Scholar

[5] M. Martinez-Ramon, J. Arenas-Garcia, A. Navia-Vazquez, etc. An adaptive combination of adaptive filters for plant identification[C]. 14th International Conference on Digital Signal Processing, Piscataway: IEEE Press (2002), p.1195.

DOI: 10.1109/icdsp.2002.1028307

Google Scholar

[6] J. Arenas-Garcia, V. Gómez-Verdejo, A.R. Figueiras-Vidal. New algorithms for improved adaptive convex combination of LMS transversal filters[J]. IEEE Trans. On Instrumentation and Measurement, Vol. 54(2005), p.2239.

DOI: 10.1109/tim.2005.858823

Google Scholar

[7] J. Arenas-Garcia, A.R. Figueiras-Vidal, A.H. Sayed. Mean-square performance of a convex combination of two adaptive filters[J]. IEEE Trans. On Signal Processing, Vol. 54(2006), p.1078.

DOI: 10.1109/tsp.2005.863126

Google Scholar