There are a number of algorithms for adaptive filters which are derived from the conventional LMS algorithm discussed in the previous chapter. The objective of the alternative LMS-based algorithms is either to reduce computational complexity or convergence time. In this chapter, several LMS-based algorithms are presented and analyzed, namely, the quantized-error algorithms –, the frequency–domain (or transform-domain) LMS algorithm –, the normalized LMS algorithm , the LMS-Newton algorithm –, and the affine projection algorithm –. Several algorithms that are related to the main algorithms presented in this chapter are also briefly discussed.
KeywordsInput Signal Convergence Speed Adaptive Filter Convergence Factor Affine Projection Algorithm
Unable to display preview. Download preview PDF.
- 4.P. Xue and B. Liu, “Adaptive equalizer using finite–bit power–of–two quantizer,” IEEE Trans, on Acoust., Speech, and Signal Processing, vol. ASSP-34, pp. 1603–1611, Dec. 1986.Google Scholar
- 14.J. C. Lee and C. K. Un, “Performance of transform–domain LMS adaptive digital filters,” IEEE Trans, on Acoust., Speech, and Signal Processing, vol. ASSP–34, pp. 499–510, June 1986.Google Scholar
- 18.S. Roy and J. J. Shynk, “Analysis of the data–reusing LMS algorithm,” Proc. Midwest Symposium on Circuits and Systems, Urbana, IL, pp. 1127–1130, Aug. 1989.Google Scholar
- 20.S. L. Gay and S. Tavathia, “The fast affine projection algorithm,” Proc. IEEE Int. Conf. on Acoust., Speech, and Signal Processing, Detroit, MI, pp. 3023–3026, May 1995.Google Scholar
- 25.N. S. Jayant and P. Noll, Digital Coding of Waveforms: Principles and Applications to Speech and Video, Prentice Hall, Englewood Cliffs, NJ, 1984.Google Scholar
- 27.A. Papoulis, Probability, Random Variables, and Stochastic Processes, 3rd edition, McGraw-Hill, New York, NY, 1991.Google Scholar
- 29.C. R. Johnson, Jr., Lectures on Adaptive Parameter Estimation, Prentice Hall, Englewood Cliffs, NJ, 1988.Google Scholar
- 36.C. S. Modlin and J. M. Cioffi, “A fast decision feedback LMS algorithm using multiple step sizes,” Proc. IEEE Inter. Conf. on Communications, New Orleans, pp. 1201–1205, May 1994.Google Scholar
- 37.S. D. Peters and A. Antoniou, “Environment estimation for enhanced NLMS adaptation,” Proc. IEEE Pac. Rim Conf. on Comm., Comp. and Sig. Proc, Victoria, Canada, pp. 342–345, May 1993.Google Scholar