Abstract

A great deal of research had been directed towards the realization of a 'fuzzy computer'. A few types of fuzzy processors which can perform various fuzzy operations, e.g. fuzzy negation, min, max and fuzzy inference, have been proposed and realized by Yamakawa [1, 2] and Togai [3]. These fuzzy inference chips have opened new opportunities for artificial intelligence. However, all of them were based on single-step fuzzy inference. In oder to realize multi-stage fuzzy inference, fuzzy memory modules are indispensable. In the case of an 'ordinary' computer, a binary flip-flop circuit, which can memorize single bits of information has been widely used as a fundamental element of memory modules.

Keywords:
Fuzzy logic Realization (probability) Adaptive neuro fuzzy inference system Computer science Fuzzy set operations Neuro-fuzzy Fuzzy electronics Defuzzification Fuzzy control system Artificial intelligence Memorization Fuzzy classification Fuzzy associative matrix Fuzzy number Arithmetic Mathematics Fuzzy set

Metrics

31
Cited By
0.85
FWCI (Field Weighted Citation Impact)
8
Refs
0.67
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Fuzzy Logic and Control Systems
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Algebra and Logic
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Neural Networks and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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