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

Bodyanskiy Yevgeniy (), Pliss Iryna () and Vynokurova Olena ()
Additional contact information
Vynokurova Olena: Kharkiv National University of Radio Electronics

Information Technology and Management Science, 2013, vol. 16, issue 1, 47-52

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.

Date: 2013
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/itms-2013-0007 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:itmasc:v:16:y:2013:i:1:p:47-52:n:7

DOI: 10.2478/itms-2013-0007

Access Statistics for this article

Information Technology and Management Science is currently edited by J. Merkurjevs

More articles in Information Technology and Management Science from Sciendo
Bibliographic data for series maintained by Peter Golla ().