A HYBRID CASCADE OPTIMIZED NEURAL NETWORK

Authors

  • O. K. Tyshchenko Control Systems Research Laboratory, Kharkiv National University of Radio Electronics, Ukraine
  • I. P. Pliss Control Systems Research Laboratory, Kharkiv National University of Radio Electronics, Ukraine
  • D. S. Kopaliani Kharkiv National University of Radio Electronics, Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2014-1-18

Keywords:

neural network, optimal learning, computational intelligence, evolving hybrid system

Abstract

A new architecture and learning algorithms for a hybrid cascade optimized neural network is proposed. The proposed hybrid system is different from existing cascade systems in its capability to operate in an online mode, which allows it to work with both non-stationary and stochastic nonlinear chaotic signals with the required accuracy. The proposed hybrid cascade neural network provides computational simplicity and possesses both tracking and filtering capabilities.

References

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Published

2014-02-21

How to Cite

Tyshchenko, O. K., Pliss, I. P., & Kopaliani, D. S. (2014). A HYBRID CASCADE OPTIMIZED NEURAL NETWORK. Radio Electronics, Computer Science, Control, (1). https://doi.org/10.15588/1607-3274-2014-1-18

Issue

Section

Neuroinformatics and intelligent systems