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Bilinear Systems and Nonlinear Estimation Theory

  • Panos M. Pardalos
  • Vitaliy Yatsenko
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 11)

In this chapter we present an application of the concept of an adaptive estimation using an estimation algebra to the study of dynamic processes in nonlinear lattice systems. It is assumed that nonlinear dynamical processes can be described by nonlinear or bilinear lattice models. Our research focuses on the development of an estimation algorithm for signal processing in the lattice models with background additive white noise. The proposed algorithm involves solution of stochastic differential equations under the assumption that the Lie algebra, associated with the processes in the lattice system, can be reduced to a finite-dimensional nilpotent algebra. A generalization is given for the case of the lattice models, which belong to a class of causal lattices with certain restrictions on input and output signals.

The chapter is organized in the following way. In Section 3.1we present the application of a method of adaptive estimation using an algebra-geometric approach, to the study of...

Keywords

Adaptive Filter Maximal Rank Adaptive Estimation Bilinear System Multisensor System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Panos M. Pardalos
    • 1
  • Vitaliy Yatsenko
    • 2
  1. 1.Department of Industrial and SystemsUniversity of FloridaGainesvilleU.S.A.
  2. 2.Institute of Space ResearchNASUKyivUkraine

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