Title :
Adaptive filtering algorithms
Author :
Theodoridis, Sergios
Author_Institution :
Dept. of Inf. & Telecommun., Athens Univ., Greece
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;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE
Conference_Location :
Budapest
Print_ISBN :
0-7803-6646-8
DOI :
10.1109/IMTC.2001.929455
