Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …

Hashing methods for efficient image retrieval aim at learning hash functions that map similar
images to semantically correlated binary codes in the Hamming space with similarity well …

The main reason of the extensive usage of the fuzzy systems in many branches of science is
their approximation ability. In this paper, an interval type-3 fuzzy system (IT3FS) is proposed …

This paper is concerned with the reliable extended passive control problem for semi-Markov
jump Takagi-Sugeno (TS) fuzzy systems based on an event-triggered mechanism (ETM). An …

Interval type-2 fuzzy neural networks (IT2FNNs) can be seen as the hybridization of interval
type-2 fuzzy systems (IT2FSs) and neural networks (NNs). Thus, they naturally inherit the …

In this paper, we first define a measure of statistical sensitivity of a zero-order Takagi–
Sugeno (TS) fuzzy neural network (FNN) with respect to perturbation of weights and …

Inspired by the life philosophy, an ingenious gate (membership) function, which can mimic
the open and close of the gate in the real world, is proposed to realize feature selection (FS) …

Throughout previous design proposals of Interval Type-2 Fuzzy Logic Systems most of the
research work concentrates on optimal design to best fit data behavior and rarely focus on …

Type-1 fuzzy sets can model the linguistic uncertainty from a single user, ie, intra-personal
uncertainty. Type-1 fuzzy systems have been widely used in controls and machine learning …

The data-driven approach is popular to automate learning of fuzzy rules and tuning
membership function parameters in fuzzy inference systems (FIS) development. However …