TY - JOUR
T1 - Architectures and algorithms for nonlinear adaptive filters
AU - Hegde, V.
AU - Radhakrishnan, C.
AU - Krusienski, D. J.
AU - Jenkins, William Kenneth
PY - 2002/1/1
Y1 - 2002/1/1
N2 - This paper considers series-cascade nonlinear adaptive filter architectures consisting of a linear input filter, a memoryless polynomial nonlinearity, and a linear output filter (LNL). The learning characteristics of the LNL structure are studied in terms of performance and complexity. Replacing the linear input stage and the memoryless nonlinear stage of the LNL model with a Volterra module is then considered. Adaptive algorithms are summarized for these structures and experimental examples are used to illustrate performance for the identification of an acoustic echo channel.
AB - This paper considers series-cascade nonlinear adaptive filter architectures consisting of a linear input filter, a memoryless polynomial nonlinearity, and a linear output filter (LNL). The learning characteristics of the LNL structure are studied in terms of performance and complexity. Replacing the linear input stage and the memoryless nonlinear stage of the LNL model with a Volterra module is then considered. Adaptive algorithms are summarized for these structures and experimental examples are used to illustrate performance for the identification of an acoustic echo channel.
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U2 - 10.1109/ACSSC.2002.1196937
DO - 10.1109/ACSSC.2002.1196937
M3 - Article
AN - SCOPUS:0038305295
SN - 1058-6393
VL - 2
SP - 1015
EP - 1016
JO - Conference Record of the Asilomar Conference on Signals, Systems and Computers
JF - Conference Record of the Asilomar Conference on Signals, Systems and Computers
ER -