• 제목/요약/키워드: Fuzzy Convergence

검색결과 500건 처리시간 0.047초

Convergence in Probability for Weighted Sums of Fuzzy Random Variables

  • Joo, Sang-Yeol;Hyun, Young-Nam
    • Communications for Statistical Applications and Methods
    • /
    • 제12권2호
    • /
    • pp.275-283
    • /
    • 2005
  • In this paper, we give a sufficient condition for convergence in probability of weighted sums of convex-compactly uniformly integrable fuzzy random variables. As a result, we obtain weak law of large numbers for weighted sums of convexly tight fuzzy random variables.

SOME GENERALIZATIONS OF SUGENOS FUZZY INTEGRAL TO SET-VALUED MAPPINGS

  • Cho, Sung-Jin;Lee, Byung-Soo;Lee, Gue-Myung;Kim, Do-Sang
    • 한국지능시스템학회:학술대회논문집
    • /
    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
    • /
    • pp.380-386
    • /
    • 1998
  • In this paper we introduce the concept of fuzzy integrals for set-valued mappings, which is an extension of fuzzy integrals for single-valued functions defined by Sugeno. And we give some properties including convergence theorems on fuzzy integrals for set-valued mappings.

  • PDF

Fuzzy c-means 알고리즘에서의 가변학습 가중치의 효과 (The Effect of Variable Learning Weights in Fuzzy c-means algorithm)

  • 박소희;조제황
    • 융합신호처리학회 학술대회논문집
    • /
    • 한국신호처리시스템학회 2001년도 하계 학술대회 논문집(KISPS SUMMER CONFERENCE 2001
    • /
    • pp.109-112
    • /
    • 2001
  • 기존의 K-means 알고리즘은 학습벡터가 단일군집에 할당되는 방법이 crisp 이므로 다른 군집에 할당될 확률을 무시하게 된다. 따라서 군집화 작업과 관련하여 반복적인 코드북 설계 과정에서 각 학습벡터를 다중 군집으로 할당하는 Fuzzy c-means를 사용한다. 또한 Fuzzy c-means 알고리즘의 학습과정에서 구해지는 각 클래스 의 프로토타입에 가중치를 곱하여 다음 학습의 프로토타입으로 사용함으로써 Fuzzy c-means 알고리즘 적용 결과 얻어지는 코트북의 성능을 기존 알고리즘과 비교하여 개선된 Fuzzy c-means 알고리즘을 찾기 위한 근거를 마련한다.

  • PDF

퍼지-슬라이딩모드 제어를 이용한 위치제어에 관한 연구 (Position Control of Fuzzy-Sliding Mode Controller)

  • 한경욱;임영도
    • 융합신호처리학회 학술대회논문집
    • /
    • 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
    • /
    • pp.221-224
    • /
    • 2000
  • We consider one of robust controller, fuzzy-sliding mode controller dealing with model uncertainty, simplified representation of nonlinear system, changed parameters of plant. We propose fuzzy-sliding mode algorithm which provides control input that has system states approaching the choosed sliding surface. This fuzzy controller has a rule base to get initial states converged on sliding surface. This algorithm Is applied to a transfer function of DC motor to be modeled simply and do position control of DC motor due to system parameters. We compare fuzzy-sliding mode controller to both sliding mode controller and fuzzy controller to identify roust control.

  • PDF

Design of Robust Fuzzy-Logic Tracker for Noise and Clutter Contaminated Trajectory based on Kalman Filter

  • Byeongil Kim
    • 한국산업융합학회 논문집
    • /
    • 제27권2_1호
    • /
    • pp.249-256
    • /
    • 2024
  • Traditional methods for monitoring targets rely heavily on probabilistic data association (PDA) or Kalman filtering. However, achieving optimal performance in a densely congested tracking environment proves challenging due to factors such as the complexities of measurement, mathematical simplification, and combined target detection for the tracking association problem. This article analyzes a target tracking problem through the lens of fuzzy logic theory, identifies the fuzzy rules that a fuzzy tracker employs, and designs the tracker utilizing fuzzy rules and Kalman filtering.

퍼지측도의 auto-연속성과 집합치 쇼케이적분 (The autocontinuity of fuzzy measures and set-valued Choquet integrals)

  • 장이채;전종덕
    • 한국지능시스템학회:학술대회논문집
    • /
    • 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
    • /
    • pp.1-3
    • /
    • 2001
  • In this paper, we define the convergence in measure and convergence in distribution for set-valued Choquet integrals. Using there definitions, we discuss convergence theorems for set-valued Choquet integrals.

  • PDF

뉴럴 네트웍 모델링에서 에러를 최소화하기 위한 퍼지분할법 (Fuzzy Division Method to Minimize the Modeling Error in Neural Network)

  • 정병묵
    • 한국정밀공학회지
    • /
    • 제14권4호
    • /
    • pp.110-118
    • /
    • 1997
  • Multi-layer neural networks with error back-propagation algorithm have a great potential for identifying nonlinear systems with unknown characteristics. However, because they have a demerit that the speed of convergence is too slow, various methods for improving the training characteristics of backpropagition networks have been proposed. In this paper, a fuzzy division method is proposed to improve the convergence speed, which can find out an effective fuzzy division by the tuning of membership function and independently train each neural network after dividing the network model into several parts. In the simulations, the proposed method showed that the optimal fuzzy partitions could be found from the arbitray initial ones and that the convergence speed was faster than the traditional method without the fuzzy division.

  • PDF

수준 연속인 퍼지 랜덤 변수의 가중 합에 대한 약 수렴성 (Weak convergence for weighted sums of level-continuous fuzzy random variables)

  • 김윤경
    • 한국지능시스템학회논문지
    • /
    • 제14권7호
    • /
    • pp.852-856
    • /
    • 2004
  • 이 논문에서는 퍼지 랜덤 변수의 합에 대한 약한 대수의 법칙을 일반화로서, 컴팩트 일양 적분 가능한 수준 연속 퍼지 랜덤 변수의 가중 합이 약 수렴하기 위한 동치 조건을 구하였다.