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Neuro-fuzzy hybridization is widely termed as fuzzy neural network (FNN) or neuro-fuzzy system (NFS) in the literature. Neuro-fuzzy system (the more popular term is used henceforth) incorporates the human-like reasoning style of fuzzy systems through the use of fuzzy sets and a linguistic model consisting of a set of IF-THEN fuzzy rules.
An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based on Takagi–Sugeno fuzzy inference system. The technique was developed in the early 1990s. [1][2] Since it integrates both neural networks and fuzzy logic principles, it has potential to capture ...
A neuro-fuzzy network is a fuzzy inference system in the body of an artificial neural network. Depending on the FIS type, several layers simulate the processes involved in a fuzzy inference-like fuzzification, inference, aggregation and defuzzification. Embedding an FIS in a general structure of an ANN has the benefit of using available ANN ...
Lotfi Zadeh was a Professor in the Graduate School of the Computer Science Division of Berkeley EECS. He also e served as the Director of BISC (Berkeley Initiative in Soft Computing). Lotfi Zadeh passed away on September 6, 2017. Zadeh was an alumnus of the University of Tehran, MIT and Columbia University.
Fuzzy cognitive maps are signed fuzzy directed graphs. Spreadsheets or tables are used to map FCMs into matrices for further computation. FCM is a technique used for causal knowledge acquisition and representation, it supports causal knowledge reasoning process and belong to the neuro-fuzzy system that aim at solving decision making problems, modeling and simulate complex systems. [4]
A fuzzy control system is a control system based on fuzzy logic —a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1, in contrast to classical or digital logic, which operates on discrete values of either 1 or 0 (true or false, respectively). [ 1 ][ 2 ] Fuzzy ...
Interval type-2 fuzzy logic systems. Type-2 fuzzy sets are finding very wide applicability in rule-based fuzzy logic systems (FLSs) because they let uncertainties be modeled by them whereas such uncertainties cannot be modeled by type-1 fuzzy sets. A block diagram of a type-2 FLS is depicted in Fig. 3.
Neuromorphic computing is an approach to computing that is inspired by the structure and function of the human brain. [ 1 ][ 2 ] A neuromorphic computer/chip is any device that uses physical artificial neurons to do computations. [ 3 ][ 4 ] In recent times, the term neuromorphic has been used to describe analog, digital, mixed-mode analog ...