• 제목/요약/키워드: Least-Square Algorithm

검색결과 891건 처리시간 0.024초

웨이브렛 패킷을 이용한 능동 소음제어 및 비교실험 (Active Noise Control by Using Wavelet Packet and Comparison Experiments)

  • 장재동;김영중;임묘택
    • 제어로봇시스템학회논문지
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    • 제13권6호
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    • pp.547-554
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    • 2007
  • This thesis presents a kind of active noise control(ANC) algorithm for reducing noise due to engine inside a car. The proposed control algorithm is, by using WP(Wavelet Packet), a one improving the instability due to delay of noise transmission and the lack of response ability for the rapid change of noise, which are defects of the existing FXLMS(Filtered-X Least Mean Square) algorithm. The chief character of this system is a thing that faster operation than the FXLMS is implemented by inserting WP in the secondary path. In other words, WP implements parallel operation. Then, the weights of filter in the adaptive algorithm will be updated faster. In addition, because WP have so excellent a resolution, they can process very minute noise. The efficiency of this control algorithm will be demonstrated in the matlab simulation and in the actual experiments by using a Labview program and a car.

ADMM for least square problems with pairwise-difference penalties for coefficient grouping

  • Park, Soohee;Shin, Seung Jun
    • Communications for Statistical Applications and Methods
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    • 제29권4호
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    • pp.441-451
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    • 2022
  • In the era of bigdata, scalability is a crucial issue in learning models. Among many others, the Alternating Direction of Multipliers (ADMM, Boyd et al., 2011) algorithm has gained great popularity in solving large-scale problems efficiently. In this article, we propose applying the ADMM algorithm to solve the least square problem penalized by the pairwise-difference penalty, frequently used to identify group structures among coefficients. ADMM algorithm enables us to solve the high-dimensional problem efficiently in a unified fashion and thus allows us to employ several different types of penalty functions such as LASSO, Elastic Net, SCAD, and MCP for the penalized problem. Additionally, the ADMM algorithm naturally extends the algorithm to distributed computation and real-time updates, both desirable when dealing with large amounts of data.

Performance of the adaptive LMAT algorithm for various noise densities in a system identification mode

  • 이영환;김상덕;조성호
    • 한국통신학회논문지
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    • 제23권8호
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    • pp.1984-1989
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    • 1998
  • Convergence properties of the stochastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criterion is presented.In particular, the performnce of the algorithmis examined and compared with least mena square (LMS) algorithm for several different probability densities of the measurement noisein a system identification mode. It is observedthat the LMAT algorithm outperforms the LMS algorithm for most of the noise probability densities, except for the case of the exponentially distributed noise.

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비동기 DS-CDMA시스템에서 RAKE 수신기를 채용한 적응형 CM 배열 안테나 (Adaptive CM Array Antenna employing RAKE Receiver in Asynchronous DS-CDMA systems)

  • 김용석;서성진;황금찬
    • 한국통신학회논문지
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    • 제29권5C호
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    • pp.601-610
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    • 2004
  • 본 논문에서는 IMT-2000 3GPP 규격의 비동기 역방향 링크 DS-CDMA 시스템에서 신호 구조 기반 Constant Modulus Algorithm (U)을 이용하는 적응 배열 안테나 RAKE 시스템의 성능을 평가한다. 또한, 참조 신호 기반 Least Mean Square (LMS)방식을 이용하는 배열 안테나 시스템과 비교한다. Monte Carlo 실험에서 다중경로, 경로간 감쇄지수, 확산이득 다중사용자 둥과 같은 환경 파라미터가 고려된다. 결과로부터 신호 전력을 분산시키는 다중 경로의 경우 CMA을 이용하는 적응 배열 안테나가 LMS를 이용하는 배열 안테나에 비해 더 큰 수용 용량을 얻을 수 있음을 알 수 있다.

실시간 가중 회기최소자승법을 사용한 익일 부하예측 (Real-Time Building Load Prediction by the On-Line Weighted Recursive Least Square Method)

  • 한도영;이재무
    • 설비공학논문집
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    • 제12권6호
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    • pp.609-615
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    • 2000
  • The energy conservation is one of the most important issues in recent years. Especially, the energy conservation through improved control strategies is one of the most highly possible area to be implemented in the near future. The energy conservation of the ice storage system can be accomplished through the improved control strategies. A real time building load prediction algorithm was developed. The expected highest and the lowest outdoor temperature of the next day were used to estimate the next day outdoor temperature profile. The measured dry bulb temperature and the measured building load were used to estimate system parameters by using the on-line weighted recursive least square method. The estimated hourly outdoor temperatures and the estimated hourly system parameters were used to predict the next day hourly building loads. In order to see the effectiveness of the building load prediction algorithm, two different types of building models were selected and analysed. The simulation results show less than 1% in error for the prediction of the next day building loads. Therefore, this algorithm may successfully be used for the development of improved control algorithms of the ice storage system.

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More Efficient Method for Determination of Match Quality in Adaptive Least Square Matching Algorithms

  • Lee, Hae-Yeoun;Kim, Tae-Jung;Lee, Heung-Kyu
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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    • pp.274-279
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    • 1998
  • For the accurate generation of DEMs, the determination of match quality in adaptive least square matching algorithm is significantly important. Traditionally, only the degree of convergence of a solution matrix in least squares estimation has been considered for the determination of match quality. It is, however, not enough to determine the true match quality. This paper reports two approaches of match quality determination based on adaptive least square correlation : the conventional if-then logic approaches with scene geometry and correlation as additional quality measures; and, the fuzzy logic approaches. Through these, accurate decision of match quality will minimize the number of blunder and maximize the number of exact match. The proposed methods have been tested on JERS and SPOT images and the results show good performance.

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Recursive Least-Square 알고리즘을 이용한 한국어 음소분류에 관한 연구 (A Study on Korean Phoneme Classification using Recursive Least-Square Algorithm)

  • 김회린;이황수;은종관
    • 한국음향학회지
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    • 제6권3호
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    • pp.60-67
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    • 1987
  • 본 논문에서는 recursive least-square(RLS) 알고리즘을 이용한 한국어 음소분류방법에 관하여 연구하였다. 각 음소의 특징벡터는 prewindowed RLS lattice 알고리즘을 사용하여 추출하는 방법을 제안하였고, 각 음소의 기준패턴은 추출된 특징벡터들을 벡터양자화하여 구성하였다. 제안된 음소인식방식의 성능시험을 위하여 한국어 음소중 자음11개와 모음 8개가 포함된 7개의 한국어 도시명을 발음하여 사용하였으며 초기의 각 음소의 기준패턴으로는 음성신호의 파형을 관찰하여 추출한 표준패턴(prototype)을 사용하였다. 컴퓨터 simulation의 결과로는 화자종속 음소인식의 경우 약간의 음소규칙을 고려할 때 약$85\%$의 음소인식율을 얻었으나, 화자독립 음소인식의 경우는 이보다 훨씬 낮은 인식율을 보였다.

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이동통신 환경에서 적응상태 축약 심볼열 추정 수신기 (The adaptive reduced state sequence estimation receiver for multipath fading channels)

  • 이영조;권성락;문태현;강창언
    • 한국통신학회논문지
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    • 제22권7호
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    • pp.1468-1476
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    • 1997
  • 상태축약심볼열추정(RSSE: Reduced State Sequence Estimation) 수신기는 비터비 복호기와 채널 추정기로 구성된다. 이동통신과 같이 채널이 변하는 환경에서는 적응 채널추정기(adaptive channel estimator)로 채널의 변화를 계속적으로 추정해야 한다. 일반적으로 사용되는 채널 추정기는 임시결정된 비터비 복호기의 출력을 사용하여 채널을 추정 하는데, 비터비 복호기에서 잘못된 결정을 내릴 경우 이로 인해 오류전파(error propagation)가 발생할 수있다. 본 논문에서는 좀더 정확한 채널 추정과 오류전파를 막기 위해 경로 메모리를 사용하는 새로운 채널추정기를 사용한다. 이 채널 추정기는 비터비 복호기의 여러 경로중에서 가장 작은 경로를 선택하여 그 경로상의 신호를 이용하여 채널 추정을 행한다. 그리고 채널 추정기의 적응 알고리듬으로서 LMS(Least Mean Square)알고리듬과 Recursive Least Square(RLS) 알고리듬을 사용하여 비교한다. 실험 결과를 통해 제안된 채널 추정기를 사용하는 RSSE 수신기가 기존의 채널 추정기를 사용하는 RSSE 수신기에 비해 더 나은 성능을 나타내는 것을 볼 수있으며, 페이딩이 존재하는 이동통신 환경에서는 LMS 알고리듬이 적합하지 않음을 알 수있다.

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Real-Time System Design and Point-to-Point Path Tracking for Real-Time Mobile Robot

  • Wang, F.H.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.162-167
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    • 2003
  • In this paper, a novel feasible real-time system was researched for a differential driven wheeled autonomous mobile robot so that the mobile robot can move in a smooth, safe and elegant way. Least Square Minimum Path Planning was well used for the system to generate a smooth executable path for the mobile robot, and the point-to-point tracking algorithm was presented as well as its application in arbitrary path tracking. In order to make sure the robot can run elegantly and safely, trapezoidal speed was integrated into the point-to-point path tracking algorithm. The application to guest following for the autonomous mobile robot shows its wide application of the algorithm. The novel design was successfully proved to be feasible by our experiments on our mobile robot Interactive Robot Usher (IRU) in National University of Singapore.

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제약조건을 갖는 최소자승 추정기법과 최급강하 알고리즘을 이용한 동적 베이시안 네트워크의 파라미터 학습기법 (Parameter Learning of Dynamic Bayesian Networks using Constrained Least Square Estimation and Steepest Descent Algorithm)

  • 조현철;이권순;구경완
    • 전기학회논문지P
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    • 제58권2호
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    • pp.164-171
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    • 2009
  • This paper presents new learning algorithm of dynamic Bayesian networks (DBN) by means of constrained least square (LS) estimation algorithm and gradient descent method. First, we propose constrained LS based parameter estimation for a Markov chain (MC) model given observation data sets. Next, a gradient descent optimization is utilized for online estimation of a hidden Markov model (HMM), which is bi-linearly constructed by adding an observation variable to a MC model. We achieve numerical simulations to prove its reliability and superiority in which a series of non stationary random signal is applied for the DBN models respectively.