Abstract
In this chapter we learn about adaptive filters that change their weights during work, from sample to sample. The filters use different adaptation equations, resulting from choice of different cost functions that are minimized during signal processing. We learn about least mean squares (LMS) adaptive filters, normalized LMS (NLMS), least squares (LS), weighted LS (WLS), and recursive LS (RLS) adaptive filters but also briefly talk about some other types. The (N)LMS filter, the most frequently used, will be in the center of our attention: we derive its adaptation rule and optimal solution in stationary state (the Wiener filter) and learn its stability criterion. We become familiar with typical application cases of adaptive filters: adaptive interference canceling (AIC), adaptive echo canceling (AEC), adaptive noise canceling (ANC), adaptive signal/line enhancement (ASE)(ALE), and adaptive telecommunication channel identification and equalization. The most popular application scenario of adaptive filters relies on correlation canceling between an information signal with additive disturbance and a reference pattern of this disturbance. Adaptive filter modifies the disturbance reference pattern, i.e. fits it (make it similar) to the actually present disturbance, and subtract from the signal. Disturbance reduction depends on the quality of performed signal correlation.
Dinosaurs failed to survive because they could not adapt to changing world. In contrary to our adaptive filter which knows how to do it.
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14 January 2022
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References
M. Bellanger, Adaptive Digital Filters (Marcel Dekker, New York, Basel, 2001)
C. Breining, et al., Acoustic echo control - An application of very high order adaptive filters. IEEE Signal Process. Mag. 16(4), 42–69 (1999)
C.F.N. Cowan, P.M. Grant, Adaptive Filters (Prentice Hall, Englewood Cliffs, 1985)
P.S.R. Diniz, Adaptive Filtering: Algorithms and Practical Implementation (Springer, New York, 2002, 2010)
B. Farhang-Boroujeny, Adaptive Filters: Theory and Applications (Wiley, New York, 2000)
G.-O. Glentis, K. Berberidis, S. Theodoridis, Efficient least squares adaptive algorithms for FIR transversal filtering. IEEE Signal Process. Mag. 16(4), 12–41 (1999)
E. Hansler, G. Schmidt, Acoustic Echo and Noise Control - A Practical Approach (Wiley, Chichester, 2004)
S. Haykin, Adaptive Filter Theory (Prentice Hall, Upper Saddle River, 1996, 2001)
S. Haykin, Modern Filters (Macmillan, New York, 1990)
G.H. Hostetter, Recursive estimation, in Handbook of Digital Signal Processing, ed. by F.D. Elliott (Academic Press, San Diego, 1987), pp. 899–940
N. Kalouptsidis, S. Theodoridis, Adaptive System Identification and Signal Processing Algorithms (Prentice Hall, New York, 1993)
S.M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory (PTR Prentice Hall, Englewood Cliffs, 1993)
S.M. Kuo, D.R. Morgan, Active Noise Control Systems: Algorithms and DSP Implementations (Wiley, New York, 1996)
K.-A. Lee, W.-S. Gan, S.M. Kuo, Subband Adaptive Filtering: Theory and Implementation (Wiley, Hoboken NJ, 2009)
D.G. Manolakis, V.K. Ingle, S.M. Kogon, Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing (McGraw-Hill, Boston, 2000; Artech House, Boston, London, 2005)
S.J. Orfanidis, Optimum Signal Processing. An Introduction (Macmillan, New York, 1988)
A.D. Poularikas, Z.M. Ramadan, Adaptive Filtering Primer with Matlab (CRC, Boca Raton, 2006)
A.H. Sayed, Adaptive Filters (Wiley-IEEE Press, New York, 2011)
A.H. Sayed, Fundamentals of Adaptive Filtering (Wiley, New York, 2003)
J. Shynk, Frequency-domain and multirate adaptive filtering. IEEE Signal Process. Mag. 10(1), 14–37 (1992)
S. Theodoridis, Adaptive filtering algorithms, in Proc. IEEE Instrumentation and Measurement Technology Conference, Budapest, 2001, pp. 1497–1501
J.R. Treichler, C.R. Johnson, M.G. Larimore, Theory and Design of Adaptive Filters (Wiley, New York, 1987)
B. Widrow, S. Stearns, Adaptive Signal Processing (Prentice Hall, Englewood Cliffs, 1985)
T.P. Zieliński, Cyfrowe Przetwarzanie Sygnalów. Od Teorii do Zastosowań (Digital Signal Processing. From Theory to Applications) (Wydawnictwa Komunikacji i Ła̧czności (Transport and Communication Publishers), Warszawa, Poland, 2005, 2007, 2009, 2014)
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Zieliński, T.P. (2021). FIR Adaptive Filters. In: Starting Digital Signal Processing in Telecommunication Engineering. Textbooks in Telecommunication Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-49256-4_12
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DOI: https://doi.org/10.1007/978-3-030-49256-4_12
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