A novel neurocomputing approach to nonlinear stochastic state estimation

  • M. B. Menhaj
  • F. Rajaii Salmasi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1226)

Abstract

This paper presents a novel neuro-computing approach to the problem of state estimation by means of an hybrid combination of Hopfield neural network whose capability of solving certain optimization problems is well-known and feedforward multilayer neural net which is very popular because of its universal approximation property. This neuro-estimator is very appropriate for the real-time implementation of linear or/and especially nonlinear state estimators. Simulation results shows the effectiveness of the proposed method.

Keywords

State Estimation Hopfield Neural Network Hopfield Network Steep Descent Algorithm Bias Input 
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.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • M. B. Menhaj
    • 1
  • F. Rajaii Salmasi
    • 1
  1. 1.Electical Engineering DepartmantAmirkabir University of TechnologyTehranIran

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