DocumentCode
1746814
Title
Adaptive filtering algorithms
Author
Theodoridis, Sergios
Author_Institution
Dept. of Inf. & Telecommun., Athens Univ., Greece
Volume
3
fYear
2001
fDate
2001
Firstpage
1497
Abstract
System identification (SI) is the task of specifying an unknown system´s model in terms of the available experimental evidence, that is a set of input-desired output response signal samples. System identification is a central issue in a large number of application areas, such as control, channel equalization, echo cancellation. This state-of-the-art article focuses on systems that can be modeled in terms of a Finite Impulse Response (FIR) and its goal is to present the available palette of adaptive SI algorithms in a unifying way
Keywords
FIR filters; adaptive filters; filtering theory; identification; adaptive filtering algorithm; finite impulse response filter; system identification; Adaptive filters; Approximation algorithms; Cost function; Filtering algorithms; Finite impulse response filter; Iterative algorithms; Least squares approximation; Stochastic processes; System identification; Wiener filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE
Conference_Location
Budapest
ISSN
1091-5281
Print_ISBN
0-7803-6646-8
Type
conf
DOI
10.1109/IMTC.2001.929455
Filename
929455
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