4. Kernel Recursive Least-Squares Algorithm

  1. Weifeng Liu,
  2. José C. Príncipe and
  3. Simon Haykin

Published Online: 5 MAR 2010

DOI: 10.1002/9780470608593.ch4

Kernel Adaptive Filtering: A Comprehensive Introduction

Kernel Adaptive Filtering: A Comprehensive Introduction

How to Cite

Liu, W., Príncipe, J. C. and Haykin, S. (2010) Kernel Recursive Least-Squares Algorithm, in Kernel Adaptive Filtering: A Comprehensive Introduction, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470608593.ch4

Publication History

  1. Published Online: 5 MAR 2010
  2. Published Print: 12 FEB 2010

ISBN Information

Print ISBN: 9780470447536

Online ISBN: 9780470608593

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Keywords:

  • kernel recursive least-squares algorithm and sparsification approach called approximate linear dependency;
  • exponentially weighted kernel recursive least-squares algorithm;
  • Gaussian processes for nonlinear regression

Summary

This chapter contains sections titled:

  • Recursive Least-Squares Algorithm

  • Exponentially Weighted Recursive Least-Squares Algorithm

  • Kernel Recursive Least-Squares Algorithm

  • Approximate Linear Dependency

  • Exponentially Weighted Kernel Recursive Least-Squares Algorithm

  • Gaussian Processes for Linear Regression

  • Gaussian Processes for Nonlinear Regression

  • Bayesian Model Selection

  • Computer Experiments

  • Conclusion

  • Endnotes