Paper Info
Title
Fuzzy nonlinear activity and dynamics of fuzzy uncertainty in the neural complex
Abstract
The studies addressed in this paper refer to the following: (i)Deducing a functional relationship between the logistic output versus input values in a neural network when the boundaries of the input and output sets are fuzzy and developing a fuzzy Riccardi differential equation (FRDE) which governs the relevant nonlinear process(es) associated with the neural complex. (ii)Evolving the dynamics of learning associated with a fuzzy neural network in terms of a fuzzy uncertainty parameter via a fuzzy Fokker–Planck equation (FFPE). The logistic growth of output versus input in the fuzzy neural complex as dictated by the FRDE, follows not only a generalized representation of a stochastically justifiable sigmoidal function (as decided by the spatial long-range order of neuronal state proliferation across the network), but it also captures the approximate nature of reasoning and perception associated with the “granular information” vis-á-vis the fuzzy set(s) of the variables involved. As regards to the solution of FRDE, it represents the function approximation of overlapping output clusters resulting from the segments of input-space grouped into membership classes (each depicting a certain range of input values). An architecture based on the fuzzy sigmoidal description of the nonlinear process(es) involved is presented and discussed.
Year
DOI
Venue
1998
10.1016/S0925-2312(98)00006-X
Neurocomputing
Keywords
Field
DocType
Fuzzy,Nonlinear activity function,Fuzzy sigmoid,Fuzzy neural dynamics
Neuro-fuzzy,Defuzzification,Fuzzy classification,Fuzzy set operations,Fuzzy logic,Fuzzy mathematics,Artificial intelligence,Fuzzy number,Membership function,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
20
1-3
0925-2312
Citations 
PageRank 
References 
0
0.34
18
Authors
4
Name
Order
Citations
PageRank
Perambur S. Neelakanta12710.35
Salahalddin T. Abusalah201.69
Dolores F. De Groff383.26
Joseph S. Park443.87