A novel neuro-fuzzy model named fuzzy broad learning system (BLS) is proposed by
merging the Takagi-Sugeno (TS) fuzzy system into BLS. The fuzzy BLS replaces the feature …

This article applies an incremental online identification algorithm to develop a set of evolving
fuzzy models (FMs) that characterize the nonlinear finger dynamics of the human hand for …

RESULTS AND CHALLENGES OF ARTIFICIAL NEURAL NETWORKS USED FOR
DECISION-MAKING AND CONTROL IN MEDICAL APPLICATIONS Adriana Albu, Page 1 …

This second edition of the must-read work in the field presents generic computational
models and techniques that can be used for the development of evolving, adaptive modeling …

In this correspondence, an online sequential fuzzy extreme learning machine (OS-fuzzy-
ELM) has been developed for function approximation and classification problems. The …

In this paper, a Sequential Adaptive Fuzzy Inference System called SAFIS is developed
based on the functional equivalence between a radial basis function network and a fuzzy …

This paper deals with a simplified version of the evolving Takagi-Sugeno (eTS) learning
algorithm-a computationally efficient procedure for on-line learning TS type fuzzy models. It …

It is a well‐known fact that nowadays we are faced not only with large data sets that we need
to process quickly, but with huge data streams. Special requirements are also placed by the …

An approach to real-time generation of fuzzy rule-base systems of extended Takagi-Sugeno
(xTS) type from data streams is proposed in the paper. The xTS fuzzy system combines both …

This paper introduces an evolving neural fuzzy modeling approach constructed upon the
neo-fuzzy neuron and network. The approach uses an incremental learning scheme to …