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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

Deadzone compensation in motion control systems using adaptive fuzzy logic control

TL;DR: The adaptive FL deadzone compensator is implemented on an actual industrial CNC machine tool to show its efficacy, guaranteeing small tracking errors and bounded parameter estimates.
Book ChapterDOI

Dynamically Reconfigurable Hardware for Evolving Bio-Inspired Architectures

TL;DR: This chapter presents a set of methodologies and architectures for exploiting the reconfigurability advantages of current commercial FPGAs in the design of bio-inspired hardware systems, among the presented architectures are neural networks, spiking neuron models, fuzzy systems, cellular automata and Random Boolean Networks.
Dissertation

Seismic risk management

Kamran Vahdat
TL;DR: In this paper, the authors applied a systematic approach to the assessment and management of seismic risk and used an integrated risk structure to address the risk of many effects of seismic events in a reliable and realistic way.
Proceedings ArticleDOI

Converting Neural Networks to Rule Foam

TL;DR: A system of rules can approximate a trained neural classifier after sampling from that classifier, and the rule base is statistically interpretable as well as modular and adaptive.
Journal ArticleDOI

Subsystem inference representation for fuzzy systems based upon product-sum-gravity rule

TL;DR: This work shows that, as the numbers of input membership functions become large, a fuzzy system with PSG inference would converge toward polynomial or Fourier series expansions, and suggests a new framework to consider fuzzy systems as universal approximators.
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.