O. K. Tyshchenko, I. P. Pliss, D. S. Kopaliani


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.


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


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