A Multidimensional Cascade Neuro-Fuzzy System with Neuron Pool Optimization in Each Cascade
Artificial Intelligence
2016-10-21 v1 Neural and Evolutionary Computing
Abstract
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.
Keywords
Cite
@article{arxiv.1610.06485,
title = {A Multidimensional Cascade Neuro-Fuzzy System with Neuron Pool Optimization in Each Cascade},
author = {Yevgeniy V. Bodyanskiy and Oleksii K. Tyshchenko and Daria S. Kopaliani},
journal= {arXiv preprint arXiv:1610.06485},
year = {2016}
}