Complex Neural Models of Dynamic Complex Systems: Study of the Global Quality Criterion and Results

  • G. Drałus
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 99)

Abstract

In this paper dynamic global models of input-output complex systems are discussed. Dynamic complex system which consists of two nonlinear discrete time sub-systems is considered. Multilayer neural networks in a dynamic structure are used as a global model. The global model is composed of two sub-models according to the complex system. A quality criterion of the global model contains coefficients which define the participation of sub-models in the global model. The main contribution of this work is the influence study on the global model quality of these coefficients. That influence is examined for different back propagation learning algorithms for complex neural networks.

Keywords

Learning Algorithm Quality Index Global Model Work Mode Dynamic Complex 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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • G. Drałus
    • 1
  1. 1.Department of Electrical Engineering FundamentalsRzeszow University of TechnologyRzeszowPoland

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