• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.50-56
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• 2001

As the fuzzy control is applied to servo system, the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$ -level set decomposition of fuzzy sets by quantize $\alpha$ -cuts. This method can be easily implemented with analog hardware. The influence of quantization Bevels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of dc servo system. The hardware implementation of proposed operation method and of the defuzzification by gravity center method which is directly converted to PWM actuating signal is also presented. It is verified useful with experiment for dc servo system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1203-1208
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• 2016

For young children who are not spontaneous or not accurate in verbal communication of their emotions and experiences, drawing is a good means of expressing their status in mind and thus drawing analysis with chromatics is a traditional tool for art therapy. Recently, children enjoy digital drawing via painting tools thus there is a growing needs to develop an automatic digital drawing analysis tool based on chromatics and art therapy theory. In this paper, we propose such an analyzing tool based on dominant color analysis. Technically, we use ART2 clustering and fuzzy logic to understand the fuzziness of subjects' status of mind expressed in their digital drawings. The frequency of color usage is fuzzified with respect to the membership functions. After applying fuzzy logic to this fuzzified central vector, we determine the dominant color and supporting colors from the digital drawings and children's status of mind is then analyzed according to the color-personality relationships based on Alschuler and Hattwick's historical researches.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.543-563
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• 1996

In this paper, we propose a Timed Fuzzy Petri Net(TFPN) model as a new model of real-time fuzzy control. The TFPN model, which is useful for fuzzy inference and fuzzy control is an integrated model of Timed PetriNet and Fuzzy Petri Net. Additionally, a Timed Fuzzy Control Language is defined as a textual specification model of fuzzy control rues, and proposed a TFPN modeling method. The TFPN model is a Petri Net formalism of fuzzy control systems. Execution rule is consisted of marking(i.e,fuzzyfication) and firing(i.e,inference and defuzzyfication) procedures. A simple case work by using TFPN model shows us computing time of inference and defuzzyfication is low and uncertainty and visibility of fuzzy control rule are modeled effectively.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.405-406
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• 2007

본 논문에서는 FCM 기반 퍼지 뉴럴네트워크 구조를 제안하고 진화 알고리즘을 이용한 FCM 기반 퍼지 뉴럴네트워크의 구조와 파라미터의 최적화 방법을 제시한다. 클러스터링 알고리즘은 퍼지 뉴럴 네트워크에서 멤버쉽함수의 중심점과 반경 등을 결정하는 학습에 일반적으로 사용된다. 제안된 FCM 기반 뉴럴 네트워크에서 멤버쉽함수는 가우시안, 삼각형 타입등의 정해진 형태를 사용하지 않고 데이터들 사이의 거리에 관계된 계산을 수행하는 FCM에 의해 결정된다. 후반부는 상수형, 선형, 2차식 등의 다양한 다항식 구조로 표현될 수 있으며 다항식의 계수는 LSE를 이용하여 결정한다. FCM 기반 퍼지 뉴럴 네트워크는 퍼지규칙의 수, 입력변수의 선택, 후반부 다항식의 차수, FCM의 퍼지화 계수의 결정은 성능에 많은 차이가 있으며 이러한 구조와 파라미터의 최적화가 요구된다. 본 논문에서는 유전자 알고리즘을 이용하여 FCM 기반 퍼지뉴럴네트워크의 구조에 관련된 입력변수의 수, 퍼지규칙의 수 그리고 후반부 다항식의 차수와 파라미터에 관련된 퍼지화 계수를 최적화 한다. 제안된 방법은 비선형 시스템의 모델링에 적용하여 성능을 분석하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1269-1274
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• 2014

In computer vision research, binarization procedure is one of the most frequently used tools to discriminate target objects from background in grey level binary image. Fuzzy binarization is a reliable technique in environment with high uncertainty such as medical image analysis by setting the threshold as the average of minimum and maximum brightness with triangle type fuzzy membership function. However, this technique is also known as contrast sensitive method thus its discrimination power is not so great when the image has low contrast difference between objects and backgrounds and suffer from information loss as a result. Thus, in this paper, we propose a fuzzy binarization using ART2 algorithm to handle such low contrast image analysis. Proposed ART2 algorithm is applied to determine the medium point of membership function in the fuzzy binarization paradigm. The proposed methods shows low information loss rate in our experiment.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.462-470
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• 2008

This study applies fuzzy functions to improve image quality under the assumption that uncertainty of image information due to low contrast is based on vagueness and ambiguity of the brightness pixel values. To solve the problem of low contrast images whose brightness distribution is inclined, we use the k-means algorithm as a parameter of the fuzzy function, through which automatic critical points can be found to differentiate objects from background and contrast between bright and dark points can be improved. The fuzzy function is presented at the three main stages presented to improve image quality: fuzzification, contrast enhancement and defuzzification. To measure improved image quality, we present the fuzzy index and entropy index and in comparison with those of histogram equalization technique, it shows outstanding performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.127-130
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• 2002

본 논문은 수학적으로 모델링하기 어려운 비선형 시스템을 위한 새로운 계층적 규칙 기반 퍼지 시스템 모델링 기법을 제안한다. 제안된 기법은 퍼지 규칙 기반 구조를 상위 규칙 기반과 하위 규칙 기반으로 나누어 계층화 시키는 것이다 계층적 퍼지 규칙을 적용함으로써 퍼지 규칙을 효율적이고 논리적으로 이용할 수 있다. 퍼지 규칙의 효율적, 논리적 사용은 퍼지 시스템의 정확성을 높일 수 있고 구조를 명료화 시킬 수 있다. 유전 알고리즘은 제안된 퍼지 규칙의 파라미터 최적화 과정에 이용된다. 가스로 데이터에 대한 퍼지 모델링 결과를 통해서 제안된 기법의 타당성 및 효용성을 검증하고 타 기법의 결과와 비교한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.9
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• pp.1718-1726
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• 2006

In this paper, we proposed a fuzzy controller and algorithm for efficiently obstacle avoidance in unknown space. The ultrasonic sensor is used for position and distance recognition of obstacle, and fuzzy controller is used for left and right wheels angular velocity control. The fuzzification is used singleton method and the control rule is each wheel forty-nine. The fuzzy inference is used simplified Mamdani's reasoning and defuzzification is used SCOG(Simplified Center Of Gravity). The computer simulation based on mobile robot modelling was performed for the capacity of fuzzy controller and the really applicable possibility revaluation of the proposed avoidance algorithm and fuzzy controller. As a result, mobile robot was exactly reached in target and it avoided obstacle efficiently.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.121-125
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• 2001

본 논문에서는 자동적인 퍼지 규칙 생성을 위해 퍼지 균등화(Fuzzy Equalization)와 유전알고리즘(Genetic Algorithm)을 이용한 TSK 퍼지 시스템의 구축을 다룬다. Pedrycz에 의해 제안된 퍼지 균등화 방법은 수치적인 데이터로부터 확률분포함수를 구축한 후 전체공간상에서 이들을 적절히 표현할 수 있는 소속함수를 생성한다. 이렇게 구축된 각 입력에 대한 소속함수는 유전알고리즘에 의해 입력공간이 분할되며 결론부 파라미터는 최소자승법에 의해 추정되어 진다. 제안된 방법은 그리드 분할로 인해 규칙의 수가 증가하는 문제를 해결하고 학습데이터와 검증데이터에 의해 타당한 입력공간분할과 퍼지 규칙을 생성할 수 있다. 시뮬레이션의 예로서 Box-Jenkins의 가스로 데이터의 모델링에 적용하여 제안된 방법의 유용성을 알 수 있다.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.73-79
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• 2003

This paper proposes speaker recognition algorithm which includes both the pitch detection and the fuzzified pattern matching. This study utilizes pitch pattern using a pitch and speech parameter uses binary spectrum. In this paper. makes reference pattern using fuzzy membership function in order to include time variation width for non-utterance time and performs vocal track recognition of common character using fuzzified pattern matching.