Chapter 2. Robust Estimation Techniques for Complex-Valued Random Vectors

  1. Tülay Adali2 and
  2. Simon Haykin3
  1. Esa Ollila and
  2. Visa Koivunen

Published Online: 16 JUN 2010

DOI: 10.1002/9780470575758.ch2

Adaptive Signal Processing: Next Generation Solutions

Adaptive Signal Processing: Next Generation Solutions

How to Cite

Ollila, E. and Koivunen, V. (2010) Robust Estimation Techniques for Complex-Valued Random Vectors, in Adaptive Signal Processing: Next Generation Solutions (eds T. Adali and S. Haykin), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470575758.ch2

Editor Information

  1. 2

    University of Maryland Baltimore County, Department of Computer Science and Electrical Engineering, Baltimore, MD, USA

  2. 3

    McMaster University, Hamilton, ON, Canada

Author Information

  1. Helsinki University of Technology, Helsinki, Finland

Publication History

  1. Published Online: 16 JUN 2010
  2. Published Print: 1 MAR 2010

Book Series:

  1. Adaptive and Learning Systems for Signal Processing, Communications, and Control

Book Series Editors:

  1. Simon Haykin

Series Editor Information

  1. McMaster University, Hamilton, ON, Canada

ISBN Information

Print ISBN: 9780470195178

Online ISBN: 9780470575758

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Keywords:

  • robust estimation techniques for complex-valued random vectors;
  • complex elliptically symmetric (CES) distributions;
  • robust ICA - class of DOGMA estimators

Summary

This chapter contains sections titled:

  • Introduction

  • Statistical Characterization of Complex Random Vectors

  • Complex Elliptically Symmetric (CES) Distributions

  • Tools to Compare Estimators

  • Scatter and Pseudo-Scatter Matrices

  • Array Processing Examples

  • MVDR Beamformers Based on M-Estimators

  • Robust ICA

  • Conclusion

  • Problems

  • References