Evolving spiking wavelet-neuro-fuzzy self-learning system

Bodyanskiy, Yevgeniy; Dolotov, Artem; Vynokurova, Olena

doi:10.1016/j.asoc.2013.05.020

Cited by 16 publications

(3 citation statements)

References 5 publications

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“…As an alternative, multiple research studies concentrate on the use of the wavelet neural network (WNN) [13][14][15][16]. Compared with the usual sigmoid function neural network, the wavelet function possesses a better learning capacity in aspects of system identification.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Wavelet Neural Network with the Improved Levenberg–Marquardt Algorithm for the AC Servo System

et al. 2021

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In this study, a fuzzy wavelet neural network with the improved Levenberg–Marquardt algorithm (FWNN-LM) is proposed to conquer nonlinearity and uncertain disturbance problems in the AC servo system. First of all, use the particle swarm optimization algorithm based on Levenberg–Marquardt (LM) to optimize parameters in the FWNN controller. Second, the potentiality of fuzzy rules (PFR) method is developed to optimize the structure of the FWNN by error reduction ratio (ERR). Furthermore, stability of FWNN-LM is proved by the Lyapunov method. Finally, simulation and prototype test results show that this method can improve the accuracy and robustness of the system in presence of load disturbances and parameter perturbations.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Wavelet Neural Network with the Improved Levenberg–Marquardt Algorithm for the AC Servo System

et al. 2021

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“…The problem of gene expression profiles filtration in these works was not considered. In the presented paper this problem is solved based on the use of wavelet analysis [17,18], which are used to process complex data in various areas of scientific research nowadays [19,20].…”

Section: Introductionmentioning

confidence: 99%

Technology of Gene Expression Profiles Filtering Based on Wavelet Analysis

Babichev¹,

Škvor²,

Fišer³

et al. 2018

IJISA

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Abstract-The paper presents the technology of gene expression profiles filtering based on the wavelet analysis methods. A structural block-chart of the wavelet-filtering process, which involves concurrent calculation of Shannon entropy for both the filtered data and allocated noise component is proposed. Simulation of the waveletfiltering process was performed with the use of orthogonal and biorthogonal wavelets on different levels of wavelet decomposition and with the use of various values of the thresholding coefficient. Result of the simulation has allowed us to propose the technology to determine the optimal parameters of the wavelet filter based on complex analysis of the filtered data and allocated noise component.

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“…The certain authors proposed to use systems of Computational Intelligence to solve this problem [1][2][3][4][5] and an area of Medical Data Mining shows increasing medical diagnostics quality. Nowadays there are many important tasks in the Medical Data Mining area, like medical diagnostics (classification, clusterization, pattern recognition and so on), compressing, prediction etc.…”

Section: Introductionmentioning

confidence: 99%

Deep Hybrid System of Computational Intelligence with Architecture Adaptation for Medical Fuzzy Diagnostics

Perova¹,

Pliss²

2017

IJISA

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Abstract-In the paper the deep hybrid system of computational intelligence with architecture adaptation for medical fuzzy diagnostics is proposed. This system allows to increase a quality of medical information processing under the condition of overlapping classes due to special adaptive architecture and training algorithms. The deep hybrid system under consideration can tune its architecture in situation when number of features and diagnoses can be variable. The special algorithms for its training are developed and optimized for situation of different system architectures without retraining of synaptic weights that have been tuned at previous steps. The proposed system was used for processing of three medical data sets (dermatology dataset, Pima Indians diabetes dataset and Parkinson disease dataset) under the condition of fixed number of features and diagnoses and in situation of its increasing. A number of conducted experiments have shown high quality of medical diagnostic process and confirmed the efficiency of the deep hybrid system of computational intelligence with architecture adaptation for medical fuzzy diagnostics.

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Evolving spiking wavelet-neuro-fuzzy self-learning system

Cited by 16 publications

References 5 publications

Fuzzy Wavelet Neural Network with the Improved Levenberg–Marquardt Algorithm for the AC Servo System

Fuzzy Wavelet Neural Network with the Improved Levenberg–Marquardt Algorithm for the AC Servo System

Technology of Gene Expression Profiles Filtering Based on Wavelet Analysis

Deep Hybrid System of Computational Intelligence with Architecture Adaptation for Medical Fuzzy Diagnostics

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