It is shown that a special case of these networks can be presented in the form of the radial basis function neural network as well as the multi-layer perceptron architecture. The neural network representations of fuzzy systems with singleton and non-singleton fuzzifier are depicted in this paper...
Fuzzy neural networks are considered as a subset of symbolic connectionism. Two critical processes involve the imposition of a knowledge base of symbolic rules into a neural network architecture and the extraction of symbolic rules from the neural network following a learning phase. During the ...
FuNN/2—a fuzzy neural network architecture for adaptive learning and knowledge acquisition Fuzzy neural networks have several features that make them well suited to a wide range of knowledge engineering applications. These strengths include fast ... NK Kasabov,J Kim,MJ Watts,... - 《Information...
The main purpose of the proposed hybrid fuzzy neural network architecture is to create self-adaptive fuzzy rules for on-line identification of a singleton or Takagi-Sugeno (TS) type (Takagi & Sugeno, 1985) fuzzy model of a nonlinear time-varying complex system. The proposed algorithm therefore ...
neural networks or fuzzy wavelet neural networks whose parameters are determined based on a purely random basis, the parameters of wavelet functions standing in FIWNs or WNs are initialized by using the C-Means clustering method. The overall architecture of the HFWNN is similar to the one of ...
In this paper, an architecture of dynamic fuzzy neural networks (D-FNN) implementing Takagi-Sugeno-Kang (TSK) fuzzy systems based on extended radial basis ... S Wu,JE Meng - 《IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man & Cyberneti...
A maximizing-discriminability-based architecture for fuzzy-neural-network (FNN) hardware is proposed in this paper. The major contribution of this proposed FNN hardware is to increase the discriminative capability among different classes in classification problems by combining linear discriminant analysis (...
This paper focuses on the evolution of Fuzzy ARTMAP neural network classifiers, using genetic algorithms, with the objective of improving generalization performance (classification accuracy of the ART network on unseen test data) and alleviating the ART category proliferation problem (the problem of creat...
Experimental Python implementation of the Clarion cognitive architecture artificial-intelligenceneural-networkscognitive-architecturecommonsense-reasoningneuro-fuzzycognitive-modelingneurosymbolic UpdatedNov 11, 2024 Python free library for clustering and neuro-fuzzy systems ...
This results in a novel fuzzy neural architecture known as the fuzzy cerebellar model articulation controller-Yager (FCMAC-Yager) system. The proposed FCMAC-Yager network exhibits learning and memory capabilities of the cerebellum through the CMAC structure while emulating the human way of reasoning ...