Proceedings of the International Conference
I W S S I P   2005

22 - 24 September 2005, Chalkida Greece
(from Chapter 1: Invited Addresses and Tutorials on Signals, Coding, Systems and Intelligent Techniques)

 Full Citation and Abstract

0 Title: Frequency Domain Adaptive Filtering in Signal Processing and Communications
  Author(s): Kosta Berberidis
  Address: Computer Engineering & Informatics, School of Engineering, University of Patras, Greece
  Reference: SSIP-SP1, 2005  pp. 37 - 37
In recent years there is an increasing interest in adaptive signal processing algorithms which are implementable in the frequency domain. Due to their computational efficiency and their good convergence properties, Frequency Domain Adaptive Filtering (FDAF) algorithms turn out to be among the most efficient solutions in several practical situations. In particular, FDAF algorithms are very useful in real-time applications involving long adaptive filters. Most of the existing FDAF algorithms are of the gradient type, that is, their time-domain counterparts are based on Least Mean Square type algorithms. However, there have been some recent efforts with promising results towards deriving frequency domain implementations of Quasi-Newton algorithms as well. The aim of this paper is to present a review of Frequency Domain Adaptive Filtering with focus on the basic ideas and tools that lead to efficient implementations. Also, modern real-time applications in signal processing and communications will be discussed, such as, Acoustic Echo Cancellation, Channel Estimation, and Channel Equalization in Single-Carrier Communication systems.

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