Fuzzy-Logic using Unary Bit-Stream Processing

There is a growing attention to the theory of fuzzy-logic and its applications. Efficient hardware design of the fuzzy-inference engine has become necessary for high-performance applications. Considering the facts that fuzzy-logic variables have truth values in the [0, 1] interval and fuzzy controll...

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Bibliographic Details
Published in2020 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 1 - 5
Main Authors Jalilvand, Amir Hossein, Najafi, M. Hassan, Fazeli, Mahdi
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2020
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Summary:There is a growing attention to the theory of fuzzy-logic and its applications. Efficient hardware design of the fuzzy-inference engine has become necessary for high-performance applications. Considering the facts that fuzzy-logic variables have truth values in the [0, 1] interval and fuzzy controllers include minimum and maximum operations, this work proposes to apply the concept of unary processing to the platform of fuzzy-logic. In unary processing, data in the [0, 1] interval is encoded as bitstream with the value defined by the frequency of 1s. Operations such as minimum and maximum functions can be implemented using simple logic gates. Latency, however, has been an important issue in the unary designs. To mitigate the latency, the proposed design processes right-aligned bit-streams. A one-hot decoder is used for fast detection of the bit-stream with maximum value. Implementing a fuzzy-inference engine with 81 fuzzy-inference rules, the proposed architecture provides 82%, 46%, and 67% saving in the hardware area, power and energy consumption, respectively, and 94% reduction in the number of used LUTs compared to conventional binary implementation.
ISBN:9781728133201
1728133203
ISSN:2158-1525
2158-1525
DOI:10.1109/ISCAS45731.2020.9180626