A HYBRID CASCADE OPTIMIZED NEURAL NETWORK
Keywords:neural network, optimal learning, computational intelligence, evolving hybrid system
AbstractA 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.
Cichocki, A. Neural Networks for Optimization and Signal Processing / A. Cichocki, R. nbehauen. – Stuttgart : Teubner, 1993. – 526 p.
Haykin, S. Neural Networks. A Comprehensive Foundation / S. Haykin. – Upper Saddle River : Prentice Hall, 1999. – 842 p.
Kasabov, N. Evolving Connectionist Systems / Kasabov N. – London : Springer-Verlag, 2003. – 307 p.
Lughofer, E. Evolving Fuzzy Systems – Methodologies, Advanced Concepts and Applications / Lughofer E. – Berlin-Heidelberg: Springer-Verlag, 2011. – 454 p.
Fahlman, S. E. The cascade-correlation learning architecture. Advances in Neural Information Processing Systems / S. E. Fahlman, C. Lebiere ; Ed. by D. S. Touretzky. – San Mateo, CA : Morgan Kaufman, 1990. – P. 524–532.
Prechelt, L. Investigation of the Cascor family of learning algorithms / Prechelt L. // Neural Networks. – 1997. – vol. 10. – P. 885–896.
Schalkoff, R. J. Artificial Neural Networks / Schalkoff R. J. – N. Y. : The McGraw-Hill Comp., 1997. – 528 p.
Avedjan, E. D. Cascade neural networks / E. D. Avedjan, G. V. Bаrkаn, I. К. Lеvin // Avtomatika i telemekhanika. – 1999. – No. 3. – P. 38–55.
Bodyanskiy, Ye. The cascaded orthogonal neural network / Ye. Bodyanskiy, A. Dolotov, I. Pliss, Ye. Viktorov ; Eds. by K. Markov, K. Ivanova, I. Mitov // Information Science & Computing. – Sofia, Bulgaria : FOI ITHEA. – 2008. – Vol. 2. – P. 13–20.
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Copyright (c) 2014 O. K. Tyshchenko, I. P. Pliss, D. S. Kopaliani
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