• Title/Summary/Keyword: MIMO fuzzy inference

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MIMO Fuzzy Reasoning Method using Learning Ability (학습기능을 사용한 MIMO 퍼지추론 방식)

  • Park, Jin-Hyun;Lee, Tae-Hwan;Choi, Young-Kiu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.10a
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    • pp.175-178
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    • 2008
  • Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

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A study of MIMO Fuzzy system with a Learning Ability (학습기능을 갖는 MIMO 퍼지시스템에 관한 연구)

  • Park, Jin-Hyun;Bae, Kang-Yul;Choi, Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.3
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    • pp.505-513
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    • 2009
  • Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

High-speed Fuzzy Inference System in Integrated GUI Environment

  • Lee, Sang-Gu
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.1
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    • pp.50-55
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    • 2004
  • We propose an intgrated Gill environment system having only integer fuzzy operations in the consequent part and the defuzzification stage. In this paper, we also propose an integrated Gill environment system with 4 parallel fuzzy processing units to be operated in parallel on the classification of the sensed image data. In this, we solve the problems of taking longer times as the fuzzy real computations of [0, 1] by using the integer pixel conversion algorithm to convert lines of each fuzzy linguistic term to the closest integer pixels. This procedure is performed automatically in the GUI application program. As a Gill environment, PCI transmission, image data pre-processing, integer pixel mapping and fuzzy membership tuning are considered. This system can be operated in parallel manner for MIMO or MISO systems.