A Multidimensional Cascade Neuro-Fuzzy System with Neuron Pool Optimization in Each Cascade
Author(s) -
Yevgeniy Bodyanskiy,
Oleksii K. Tyshchenko,
Daria S. Kopaliani
Publication year - 2014
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2014.08.02
Subject(s) - cascade , computer science , chaotic , process (computing) , artificial intelligence , simplicity , artificial neural network , chemistry , chromatography , philosophy , epistemology , operating system
A new architecture and learning algorithms for the multidimensional hybrid cascade neural network with neuron pool optimization in each cascade are proposed in this paper. The proposed system differs from the well-known cascade systems in its capability to process multidimensional time series in an online mode, which makes it possible to process non- stationary stochastic and chaotic signals with the required accuracy. Compared to conventional analogs, the proposed system provides computational simplicity and possesses both tracking and filtering capabilities.
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