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Hybrid adaptive wavelet-neuro-fuzzy system for chaotic time series identification
In the paper a five-layers architecture of hybrid wavelet-neuro-fuzzy system which is using the adaptive W-neurons as the nodes is proposed. Expand
Single-frame image super-resolution based on singular square matrix operator
In the paper the method of single-frame image super-resolution based on the singular decomposition of matrix operator of the convergence square matrix operator is proposed. The characteristicExpand
An adaptive learning algorithm for a wavelet neural network
: An optimal online learning algorithm of a wavelet neural network is proposed. Expand
Hybrid Multidimensional Wavelet-Neuro-System and its Learning Using Cross Entropy Cost Function in Pattern Recognition
In this paper, the hybrid multidimensional wavelet-neuro-system for pattern recognition tasks is proposed. Expand
A Novel Ensemble Neuro-Fuzzy Model for Financial Time Series Forecasting
A novel ensemble neuro-fuzzy model is proposed to overcome limitations and improve the previously successfully applied five-layer multidimensional Gaussian neuro- fuzzy models and its learning. Expand
Adaptive wavelet diagnostic neuro-fuzzy network for biomedical tasks
In this article, a new adaptive wavelet diagnostic neuro-fuzzy network (AWDNFN) based on additive generalized neuro-models and the adaptive W-neuron is proposed. Expand
Associative Probabilistic Neuro-Fuzzy System for Data Classification Under Short Training Set Conditions
The paper proposes a classifying neuro-fuzzy system intended for operating under short training set and nonconvex classes conditions. Expand
Adaptive multivariate hybrid neuro-fuzzy system and its on-board fast learning
In the paper the multivariate adaptive hybrid neuro-fuzzy system is proposed that allows to process nonstationary information disturbed by noises in sequential mode and also has smaller number of tuned parameters comparatively with known neuro- fuzzy systems. Expand
Fast learning algorithm for deep evolving GMDH-SVM neural network in data stream mining tasks
In the paper, the deep evolving neural network and its learning algorithms (in batch and on-line mode) are proposed. Expand