Chapter 1: Invited Addresses and Tutorials on Signals, Coding,
  Systems and Intelligent Techniques

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: 12th International Workshop on Systems, Signals and Image Processing pp. 37 - 37

Abstract/Summary: 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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