UCLA Extension

Adaptive Filters

Adaptive systems have evolved rapidly over the last three decades as a result of significant advances in integrated circuit design and digital computer technology. The falling cost of hardware and software has made it possible to pursue sophisticated signal processing designs at relatively low cost. So it is no surprise that adaptive filters have become prominent elements in many modern applications, from biomedical engineering to consumer products to communications and military electronics. In particular, the explosive interest in communications applications, including wireless networks, voice over IP, HDTV, DSL, echo cancellation, home-phone networking, and channel equalization, has led to a heightened interest in understanding the limits of performance of existing adaptive filters and in developing variants that meet stringent specifications.

This course provides an up-to-date introduction to the fundamentals of adaptive filtering, with emphasis on applications in the fields of signal processing and communications as well as on potential connections with other filtering methodologies. The course is designed to edify both professionals with limited exposure to the field and practitioners who seek a systematic and unifying exposition of the topic. Emphasis is on fundamental ideas and on potential applications.

The course addresses:

  • How much faster can an adaptive filter be made to converge, and also track signal variations, without compromising stability?
  • How do we choose among the wide variety of adaptive structures that are available and/or how do we adjust them to specific needs?
  • How do we develop adaptive structures that attend to the increasing demand of higher performance at lower complexity?

Special Feature: Computer Demonstrations

The course includes examples and computer demonstrations on adaptive filter analysis and design, allowing participants to work with typical applications in signal processing and digital communications, including equalization, echo cancellation, channel estimation, OFDM receivers, and RAKE receivers.

Course Materials

The text, Fundamentals of Adaptive Filtering, A.H. Sayed (Wiley, 2003), and copies of the course slides are distributed on the first day of the course. The slide copies are for participants only and are not for sale.

Coordinator and Lecturer

A.H. Sayed, PhD, Professor, Department of Electrical Engineering, Henry Samueli School of Engineering and Applied Science, UCLA. Professor Sayed is the Principal Investigator of the UCLA Adaptive Systems Laboratory and a leading authority in the field of adaptive filtering. He has consulted to several companies on issues related to adaptive filter design, echo cancellation, and channel equalization. He has authored and coauthored four books on different aspects of filtering and estimation algorithms, including the course text, and also has published widely in conference proceedings, archival journals, and encyclopedia volumes. Dr. Sayed sits on the editorial boards of several journal publications and serves as Editor-in-Chief of the IEEE Transactions on Signal Processing. He is a Fellow of IEEE for his contributions to adaptive filtering and estimation algorithms. His work on adaptive filtering has been awarded the 1996 IEEE Donald G. Fink Award and the 2002 Best Paper Award in the area of Signal Processing Theory and Methods from the IEEE Signal Processing Society.

Daily Schedule

Day 1

The Estimation Paradigm

Fundamentals of Linear Estimation

Examples

  • Channel estimation
  • Linear channel equalization
  • Decision feedback equalization
  • Beamforming

Steepest Descent Algorithms

The Family of LMS Algorithms

Examples

  • Adaptive channel estimation
  • Adaptive channel equalization

Day 2

Applications of Adaptive Filters

  • Channel estimation
  • Inverse modeling
  • Channel equalization
  • Interference cancellation
  • Echo cancellation
  • Line enhancement
  • Noise canceller

Performance of Adaptive Filters

  • Mean-square performance
  • Tracking performance
  • Convergence rate
  • Misadjustment
  • Finite precision effects

Day 3

Least-Squares Methods

Recursive Least-Squares

Array Methods

Fast Least-Squares Methods

Lattice Filters

Examples

  • Comparison with LMS
  • RLS implementations

Discussion of Problems of Interest to Participants

Software Demonstrations: Opportunity for Participants to Exercise with Typical Applications in the Context of Digital Communications

  • Experiment 1-Adaptive channel equalization and channel estimation: Design of LMS adaptive filters for improving data transmission over a communication channel. Participants compare different filter implementations and parameter selections.
  • Experiment 2-Adaptive blind equalization: Design and comparison of blind adaptive equalizers for improving data transmission over a communication channel.
  • Experiment 3-Adaptive line echo cancellation: Design of adaptive structures for line echo cancellation. Selection of parameters and comparison among filter implementations.
  • Experiment 4-OFDM and RAKE receivers: Design of least-squares and least-mean-squares receivers for both OFDM and CDMA transmissions.

For more information contact the Short Course Program Office:
shortcourses@uclaextension.edu | (310) 825-3344 | fax (310) 206-2815

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