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Publikācija: Flexible Neo-fuzzy Neuron and Neuro-fuzzy Network for Monitoring Time Series Properties

Publication Type Publications in RTU scientific journal
Funding for basic activity Unknown
Defending: ,
Publication language English (en)
Title in original language Flexible Neo-fuzzy Neuron and Neuro-fuzzy Network for Monitoring Time Series Properties
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Authors Yevgeniy Bodyanskiy
Iryna Pliss
Olena Vynokurova
Keywords Flexible activation-membership function, flexible neo-fuzzy neuron, forecasting, identification learning algorithm
Abstract In the paper, a new flexible modification of neofuzzy neuron, neuro-fuzzy network based on these neurons and adaptive learning algorithms for the tuning of their all parameters are proposed. The algorithms are of interest because they ensure the on-line tuning of not only the synaptic weights and membership function parameters but also forms of these functions that provide improving approximation properties and allow avoiding the occurrence of “gaps” in the space of inputs.
DOI: 10.2478/itms-2013-0007
Reference Bodyanskiy, Y., Pliss, I., Vynokurova, O. Flexible Neo-fuzzy Neuron and Neuro-fuzzy Network for Monitoring Time Series Properties. Information Technology and Management Science. Vol.16, 2013, pp.47-52. ISSN 22559086.
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