• 제목/요약/키워드: Forgetting

검색결과 164건 처리시간 0.023초

이동 jammer 환경에 대응할 수 있는 가변 망각 인자 적응 빔형성 기법 (Adapt ive beamforming technique with variable forgetting factor in moving jammer environments)

  • 송준일;김윤정;임준석;성굉모
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2001년도 추계학술발표대회 논문집 제20권 2호
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    • pp.361-364
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    • 2001
  • 지금까지 수중음향 시스템에서 jammer 신호를 제거하는 방법에 관한 많은 연구가 진행되어 왔다. 그러나, 기존의 빔형성 기법은 간섭 신호원(interference source)이 움직일 경우 그 성능이 현저히 떨어지는 문제점을 갖고 있다. 이러한 현상은 수중 음향 시스템이 간섭 신호원의 움직임에 대하여 즉각적으로 null의 위치를 변화시키지 못하기 때문에 발생하게 된다. 이를 해결하기 위해서는 시간에 따라 위치가 변하는 jammer 환경에 대하여 대응할 수 있는 새로운 알고리즘이 필요하게 된다. 이러한 단점을 보완하기 위해 본 논문에서는 가변 망각인자를 갖는 적응 빔형성 기법을 제안하고, 컴퓨터 모의실험을 통하여 제안된 알고리즘이 기존의 적응 빔형성 기법에 비하여 출력 SINR(signal to interference plus noise ratio)의 측면에서 성능 향상을 가짐을 보였다.

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능동소음제어를 위한 안정화된 퍼지 LMS 알고리즘 (Stabilized Adaptive Fuzzy LMS Algorithms for Active Noise Control)

  • 안동준;백광현;남현도
    • 전기학회논문지
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    • 제60권1호
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    • pp.150-155
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    • 2011
  • In an active noise control systems, an IIR filter may cause a problem in stability beacause of its poles. For IIR filter, its poles goes sometimes out of a unit circle in a z-plane in the transition state, where the adaptive algorithm converges to the optimum value, which causes the system to diverge. Fuzzy LMS algorithm has a better convergence property than conventional LMS algorithms, but is not applicable to IIR filter because of the reasons. Stabilized adaptive algorithm could be improves stability by moving the pole of IIR filer toward the origin forcibly in the transient state, and by introducing forgetting factor to maintain the optimum convergence when it reaches to the steady state. In this paper, We proposed stabilized adaptive fuzzy LMS algorithms with IIR filter structures, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithm.

순환최소자승법을 이용한 직류도시철도 변전소의 가선전압변동 모델링 (Modelling Voltage Variation at DC Railway Traction Substation using Recursive Least Square Estimation)

  • 배창한
    • 전력전자학회논문지
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    • 제20권6호
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    • pp.534-539
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    • 2015
  • The DC overhead line voltage of an electric railway substation swings depending on the accelerating and regenerative-braking energy of trains, and it deteriorates the energy quality of the electric facility in the DC railway substation and restricts the powering and braking performance of subway trains. Recently, an energy storage system or a regenerative inverter has been introduced into railway traction substations to diminish both the variance of the overhead line voltage and the peak power consumption. In this study, the variance of the overhead line voltage in a DC railway substation is modelled by RC parallel circuits in each feeder, and the RC parameters are estimated using the recursive least mean square (RLMS) scheme. The forgetting factor values for the RLMS are selected using simulated annealing optimization, and the modelling scheme of the overhead line voltage variation is evaluated through raw data measured in a downtown railway substation.

안전벨트 착용과정에서 무의식적 행위와 착용비율 (Seat Belt Usage Rate and Unconscious Behavior in the Fastening Process)

  • 홍승권
    • 대한인간공학회지
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    • 제29권6호
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    • pp.959-964
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    • 2010
  • Seat belt is an important means to protect drivers and passengers from the damages by car accidents. Many ways to increase the seat belt wearing rate have been proposed through human factors researches. The primary ways to increase seat belt use rate have emphasized the intention-behavior cycle. This study focused on the gap between intention and behavior. The gap may be bridged by the habit for seat belt use behavior. Divers following a desirable car starting sequence, from sitting on the chair, fastening seat belt, starting engine to moving a car, reported that higher belt wearing rate and unconscious behavior (automated response). That is, the habitualized procedure knowledge prevented drivers from forgetting to fasten their seat belt. The reminder systems such as warning light and warning sound could not significantly give an influence in remembering to fasten seat belt. In order to increase the seat belt use rate, the desirable car starting procedure should be included in the driving education program.

직접파와 coherent 반사파가 있는 시변 DOA추정을 위한 순차적 신호 부공간 추정 기법 연구 (Forward Backward VFF-PASTd Algorithm for the Direct and Reflected Signal Environments)

  • 임준석;편용국;윤석준
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2002년도 하계학술발표대회 논문집 제21권 1호
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    • pp.237-240
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    • 2002
  • 지면에 가까이 있는 비행체나 수면에 가까이 있는 수중 운동체에서 도래하는 신호는 직접파와 반사파로 구성되어 있다. 그런 환경에서는 반사파가 직접파와 coherent한 관계를 갖는다. 이런 현상으로 해서 DOA추정을 위해 추정한 correlation 행렬이 singular한 성질을 갖게 된다. 이렇게 singular한 행렬은 DOA추정에 큰 오류를 내게 된다. 또 움직이는 대상의 경우 추정 correlation 행렬의 성질이 시간에 따라 변하게 된다. 본 논문에서는 위 두 상황을 함께 해결하기 위해서 PASTd알고리즘을 변형하여 Forward/Backward Variable forgetting factor를 도입한 PASTd알고리즘을 제안한다.

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예측 적응제어 기법을 이용한 전기 유압 모터의 제어에 관한 연구 (A Study on the Control of Electro-Hydraulic Motors Using Ahead Predictive Adaptive Control Method)

  • 김병우;허진
    • 전기학회논문지
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    • 제60권7호
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    • pp.1360-1365
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    • 2011
  • Electro-hydraulic servo motor is used to a lot of in the field of industrial equipment which requires one of the control functions among pressure, flow, and power output. In this paper, linear discrete reference model of the electro-hydraulic servo motor system are made for 1-step ahead predictive control. The parameters of electro-hydraulic servo motor system are estimated using the recursive least square method. 1-step ahead predictive model output of electro-hydraulic servo motor system corresponded to reference model output in spite of estimated parameters are not meet real parameters. Control performance affections are studied due to the forgetting factors variation.

A Ship Intelligent Anti-Collision Decision-Making Supporting System Based On Trial Manoeuvre

  • Zhuo, Yongqiang;Yao, Jie
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2006년도 Asia Navigation Conference
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    • pp.176-183
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    • 2006
  • A novel intelligent anti-collision decision-making supporting system is addressed in this paper. To obtain precise anti-collision information capability, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. This neurofuzzy network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge. This supporting system can decrease ship operators' burden to deal with bridge data and help them to make a precise anti-collision decision.

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Feature Transformation based Music Retrieval System

  • Heo, Jung-Im;Yang, Jin-Mo;Kim, Dong-Hyun;Yoon, Kyoung-Ro;Kim, Won-Il
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권3호
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    • pp.192-195
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    • 2008
  • People have tendency of forgetting music title, though they easily remember particular part of music. If a music search system can find the title through a part of melody, this will provide very convenient interface to users. In this paper, we propose an algorithm that enables this type of search using feature transformation function. The original music is transformed to new feature information with sequential melodies. When a melody that is a part of search music is given to the system, the music retrieval system searches the music similar to the feature information of the melody. Moreover, this transformation function can be easily extended to various music recognition systems.

Intelligent fuzzy weighted input estimation method for the input force on the plate structure

  • Lee, Ming-Hui;Chen, Tsung-Chien
    • Structural Engineering and Mechanics
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    • 제34권1호
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    • pp.1-14
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    • 2010
  • The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthesize the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The capability of this inverse method are demonstrated in the input force estimation cases of the plate structure system. The proposed algorithm is further compared by alternating between the constant and adaptive weighting factors. The results show that this method has the properties of faster convergence in the initial response, better target tracking capability, and more effective noise and measurement bias reduction.

에빙하우스 망각 곡선 기반 개선된 온라인 교육 시스템 (Improved Online Educational System based on Ebbinhaus's Forgetting Curve)

  • 김분희
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2009년도 춘계학술발표대회
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    • pp.1006-1008
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    • 2009
  • 온라인 교육 시스템에서 사용자는 효과적인 학습을 위해 향상된 교육 컨텐츠를 이용하고자 한다. 온라인 교육 시스템은 다양한 알고리즘을 프로그래밍하여 개별 사용자에게 적합한 구성이 가능하다. 이러한 온라인 교육 시스템은 미리 짜여진 프로그램에 의한 체계적인 반복 교육에 적합하다. 사용자의 효과적인 학습을 측정하는데 있어 학습한 내용이 장기기억 되는 방법의 적용은 무엇보다 중요하다. 본 논문에서는 학습한 내용의 기억 추이를 나타내는 에빙하우스 망각 곡선 이론을 기반으로 학습 시스템의 장기 기억 메커니즘을 구현하고자 한다. 본 논문에서 제안한 온라인 교육 시스템의 학습 내용은 학습자의 장기 기억된 정도를 측정함으로써 그 효용성을 나타낸다.