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Journal ArticleDOI

Fuzzy systems as universal approximators

Bart Kosko
- 01 Nov 1994 - 
- Vol. 43, Iss: 11, pp 1329-1333
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TLDR
An additive fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy.
Abstract
An additive fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. An additive fuzzy system approximates the function by covering its graph with fuzzy patches in the input-output state space and averaging patches that overlap. The fuzzy system computes a conditional expectation E|Y|X| if we view the fuzzy sets as random sets. Each fuzzy rule defines a fuzzy patch and connects commonsense knowledge with state-space geometry. Neural or statistical clustering systems can approximate the unknown fuzzy patches from training data. These adaptive fuzzy systems approximate a function at two levels. At the local level the neural system approximates and tunes the fuzzy rules. At the global level the rules or patches approximate the function. >

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Citations
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Proceedings ArticleDOI

Elliptec Piezo electric motor: Modeling and control using fuzzy approaches

TL;DR: The aim of this paper is to present a suitable model of an ultrasonic motor, Elliptec, and also an intelligent speed control algorithm based on fuzzy inverse model of the motor in an adaptive Internal Model Control (IMC) structure.
Proceedings ArticleDOI

Particle swarm optimization with turbulence (PSOT) applied to thermal-vacuum modelling

TL;DR: Particle Swarm Optimization with Turbulence (PSOT) is applied to find out fuzzy models to represent dynamic behavior of space systems that lie underneath the space qualification process by taking into account the velocity of convergence to better solution and the total optimization time in generating dynamical models to the proposed system.
Proceedings ArticleDOI

Evaluation of a fuzzy system-based automotive copilot dedicated to lateral guidance

TL;DR: Encouraging results from field-test experiments based on drivers' point of view are presented, taking benefit from a positive cooperation of fuzzy logic and ergonomics.
Proceedings ArticleDOI

Methodology for adapting the parameters of a fuzzy system using the extended Kalman filter

TL;DR: The application of extended Kalman filter for the parametric adaptation of a fuzzy model is presented and it is shown that the results obtained are satisfactory for fuzzy model adaptation.
Dissertation

Al-based robust multi-regime controller

TL;DR: A way to derive a robust controller which accounts for uncertainty decoupling and controller's effort awareness is presented and a fuzzy scheduling scheme (using accc)mplishment membership functions) is added to that cascaded robust topology to achieve multi-regime control.
References
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Journal ArticleDOI

Multilayer feedforward networks are universal approximators

TL;DR: It is rigorously established that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.
Book

Functional analysis

Walter Rudin
Book

Fuzzy Sets and Systems: Theory and Applications

Didier Dubois, +1 more
TL;DR: This book effectively constitutes a detailed annotated bibliography in quasitextbook style of the some thousand contributions deemed by Messrs. Dubois and Prade to belong to the area of fuzzy set theory and its applications or interactions in a wide spectrum of scientific disciplines.
Journal ArticleDOI

Fuzzy basis functions, universal approximation, and orthogonal least-squares learning

TL;DR: Using the Stone-Weierstrass theorem, it is proved that linear combinations of the fuzzy basis functions are capable of uniformly approximating any real continuous function on a compact set to arbitrary accuracy.