Open AccessBook
On fuzzy algorithms
Lotfi A. Zadeh
- pp 127-147
TLDR
A fuzzy algorithm is introduced which, though fuzzy rather than precise in nature, may eventually prove to be of use in a wide variety of problems relating to information processing, control, pattern recognition, system identification, artificial intelligence and, more generally, decision processes involving incomplete or uncertain data.Abstract:
Unlike most papers in Information and Control, our note contains no theorems and no proofs. Essentially, its purpose is to introduce a basic concept which, though fuzzy rather than precise in nature, may eventually prove to be of use in a wide variety of problems relating to information processing, control, pattern recognition, system identification, artificial intelligence and, more generally, decision processes involving incomplete or uncertain data. The concept in question will be called a fuzzy algorithm because it may be viewed as a generalization, through the process of fuzzification, of the conventional (nonfuzzy) conception of an algorithm. More specifically, unlike a nonfuzzy deterministic or nondeterministic algorithm (Floyd, 1967), a fuzzy algorithm may contain fuzzy statements, that is, statements containing names of fuzzy sets (Zadeh, 1965), by which we mean classes in which there may be grades of membership intermediate between full membership and nonmembership. To illustrate, fuzzy algorithms may contain fuzzy instructions such as:read more
Citations
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Outline of a New Approach to the Analysis of Complex Systems and Decision Processes
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Fuzzy Set Theory - and Its Applications
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An introduction to multisensor data fusion
David L. Hall,James Llinas +1 more
TL;DR: This paper provides a tutorial on data fusion, introducing data fusion applications, process models, and identification of applicable techniques.
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A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
TL;DR: A survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models.
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The role of fuzzy logic in the management of uncertainty in expert systems
TL;DR: F fuzzy logic is suggested, which is the logic underlying approximate or, equivalently, fuzzy reasoning, which leads to various basic syllogisms which may be used as rules of combination of evidence in expert systems.
References
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Book
A view of programming languages
Bernard A. Galler,Alan J. Perlis +1 more
TL;DR: In this paper, the authors present a course in computer programming at the graduate level, suitable for undergraduates as well as graduates interested in the design of programming languages and in the implementation of language processors.