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Additional resources for Adaptive Filtering
13] J. H. Husøy and M. S. E. Abadi, “Unified approach to adaptive filters and their performance,” IET Signal Processing, vol. 2, pp. , 2008.  T. Y. Al-Naffouri and A. H. Sayed, “Transient analysis of adaptive filters with error nonlinearities,” IEEE Trans. Signal Processing, vol. 51, pp. , 2003.  O. Dabeer, and E. Masry, “Analysis of mean-square error and transient speed of the LMS adaptive algorithm,” IEEE Trans. Information Theory, vol. 48, pp. 1873-1894, July, 2002.  N. J. Bershad, J.
17 (1), pp. , 2007.  B. Lin, R. He, X. Wang and B. Wang, “The steady-state mean square error analysis for least mean p-order algorithm,” IEEE Signal Processing Letter, vol. 16, pp. 176-179, 2009. 3 The Ultra High Speed LMS Algorithm Implemented on Parallel Architecture Suitable for Multidimensional Adaptive Filtering Marwan Jaber Université du Québec à Trois-Rivières Canada 1. Introduction Over the past decades a number of new adaptive filter algorithms have been elaborated and applied to meet demands for faster convergence and better tracking properties than earlier techniques could offer.
Stearns, Adaptive Signal Processing, Prentice Hall, Englewood Cliffs, NJ, 1988.  A. I. Sulyman and A. Zerguine, Convergence and steady-state analysis of a variable step-size NLMS algorithm, ELSEVIER Signal Processing, Vol. 83, , pp. 1255-1273, 2003.  H. Takekawa. T. Shimamura, and S. A. Jimaa, “An efficient and effective variable step size NLMS algorithm”, 42nd Asilomar conference on signals, systems and computers, CA, USA, October 26-29, 2008.  Ling Quin and M. G. Bellanger,” Convergence analysis of a variable step-size normalized adaptive filter algorithm”, Proc.
Adaptive Filtering by L. Morales