• 제목/요약/키워드: Gradient Algorithm

검색결과 1,158건 처리시간 0.027초

고속순차 최소자승법에 의한 선형위상 유한응답 여파기의 설계 (Fast Sequential Least Squares Design of FIR Filters with Linear Phase)

  • 선우종성
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1987년도 학술발표회 논문집
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    • pp.79-81
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    • 1987
  • In this paper we propose a fast adaptive least squares algorithm for linear phase FIR filters. The algorithm requires 10m multiplications per data point where m is the filter order. Both linear phase cases with constant phase delay and constant group delay are examined. Simulation results demonstrate that the proeposed algorithm is superior to the LMS gradient algorithm and the averaging scheme used for the modified fast Kalman algorithm.

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가속화 알고리즘을 이용한 EBP의 학습 속도의 개선에 관한 연구 (A study on the improvement of the EBP learning speed using an acceleration algorithm)

  • 최희창;귄희용;황희융
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1989년도 하계종합학술대회 논문집
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    • pp.457-460
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    • 1989
  • In this paper, an improvement of the EBP(error back propagation) learning speed using an acceleration algorithm is described. Using an acceleration algorithm known as the Partan method in the gradient search algorithm, learning speed is 25% faster than the original EBP algorithm in the simulaion results.

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Implementation of Speed Sensorless Induction Motor drives by Fast Learning Neural Network using RLS Approach

  • Kim, Yoon-Ho;Kook, Yoon-Sang
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 1998년도 Proceedings ICPE 98 1998 International Conference on Power Electronics
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    • pp.293-297
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    • 1998
  • This paper presents a newly developed speed sensorless drive using RLS based on Neural Network Training Algorithm. The proposed algorithm has just the time-varying learning rate, while the wellknown back-propagation algorithm based on gradient descent has a constant learning rate. The number of iterations required by the new algorithm to converge is less than that of the back-propagation algorithm. The theoretical analysis and experimental results to verify the effectiveness of the proposed control strategy are described.

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어닐링에 의한 Hierarchical Mixtures of Experts를 이용한 시계열 예측 (Prediction of Time Series Using Hierarchical Mixtures of Experts Through an Annealing)

  • 유정수;이원돈
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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    • pp.360-362
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    • 1998
  • In the original mixtures of experts framework, the parameters of the network are determined by gradient descent, which is naturally slow. In [2], the Expectation-Maximization(EM) algorithm is used instead, to obtain the network parameters, resulting in substantially reduced training times. This paper presents the new EM algorithm for prediction. We show that an Efficient training algorithm may be derived for the HME network. To verify the utility of the algorithm we look at specific examples in time series prediction. The application of the new EM algorithm to time series prediction has been quiet successful.

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A Fast Normalized Cross Correlation-Based Block Matching Algorithm Using Multilevel Cauchy-Schwartz Inequality

  • Song, Byung-Cheol
    • ETRI Journal
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    • 제33권3호
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    • pp.401-406
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    • 2011
  • This paper presents a fast block-matching algorithm based on the normalized cross-correlation, where the elimination order is determined based on the gradient magnitudes of subblocks in the current macroblock. Multilevel Cauchy-Schwartz inequality is derived to skip unnecessary block-matching calculations in the proposed algorithm. Also, additional complexity reduction is achieved re-using the normalized cross correlation values for the spatially neighboring macroblock because the search areas of adjacent macroblocks are overlapped. Simulation results show that the proposed algorithm can improve the speed-up ratio up to about 3 times in comparison with the existing algorithm.

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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경사법에의한 최적제어 (Optimal Control by the Gradient Method)

  • 양흥석;황희융
    • 전기의세계
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    • 제21권3호
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    • pp.48-52
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    • 1972
  • The application of pontryagin's Maximum Principle to the optimal control eventually leads to the problem of solving the two point boundary value problem. Most of problems have been related to their own special factors, therfore it is very hard to recommend the best method of deriving their optimal solution among various methods, such as iterative Runge Kutta, analog computer, gradient method, finite difference and successive approximation by piece-wise linearization. The gradient method has been applied to the optimal control of two point boundary value problem in the power systems. The most important thing is to set up some objective function of which the initial value is the function of terminal point. The next procedure is to find out any global minimum value from the objective function which is approaching the zero by means of gradient projection. The algorithm required for this approach in the relevant differential equations by use of the Runge Kutta Method for the computation has been established. The usefulness of this approach is also verified by solving some examples in the paper.

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향상된 Gradient Inverse Weighted Filter를 적용한 디인터레이싱 알고리듬 (Deinterlacing Algorithm Using New Gradient Inverse Weighted Filter)

  • 윤장혁;유종상;전광길;정제창
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2013년도 하계학술대회
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    • pp.260-262
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    • 2013
  • 본 논문에서는 gradient inverse weighted filtering(GIWF) 보간법 기반의 화면 내 디인터레이싱 알고리듬을 제안한다. 소실된 화소 줄을 보간하기 위해서 먼저 선 처리 과정을 통해 정해진 마스크의 중간 지점의 예측 값을 생성한다. 이 때는 4-tap 필터를 이용을 한다. 다음으로 이웃 픽셀들 사이에서 마스크 내의 기울기 정보를 이용하여 gradient-weighted 필터의 가중치 계수를 계산한다. 그리고 마지막으로 새롭게 제시된 GIWF 보간법을 이용하여 소실된 화소 줄을 보간하게 된다. GIWF를 이용하여 영상의 디테일을 보존하고 잡음을 제거하는 효과를 얻게 되었다. 제안된 방법의 영상 시퀀스에 대한 실험 결과는 기존의 방법들에 비하여 성능의 우수함을 보여준다.

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수정완경사방정식을 위한 반복기법의 효율성 비교 (Efficient Iterative Solvers for Modified Mild Slope Equation)

  • 윤종태;박승민
    • 한국해양공학회지
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    • 제20권6호
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    • pp.61-66
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    • 2006
  • Two iterative solvers are applied to solve the modified mild slope equation. The elliptic formulation of the governing equation is selected for numerical treatment because it is partly suited for complex wave fields, like those encountered inside harbors. The requirement that the computational model should be capable of dealing with a large problem domain is addressed by implementing and testing two iterative solvers, which are based on the Stabilized Bi-Conjugate Gradient Method (BiCGSTAB) and Generalized Conjugate Gradient Method (GCGM). The characteristics of the solvers are compared, using the results for Berkhoff's shoal test, used widely as a benchmark in coastal modeling. It is shown that the GCGM algorithm has a better convergence rate than BiCGSTAB, and preconditioning of these algorithms gives more than half a reduction of computational cost.

고성능 DSP를 이용한 영상기울기 검출 시스템 구현에 관한 연구 (Implementation of Image Gradient Detection System with High-Performance DSP)

  • 이승준;이상범
    • 한국컴퓨터산업학회논문지
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    • 제9권3호
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    • pp.129-136
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    • 2008
  • 본 논문은 NTSC 카메라로 부터 획득한 컬러 이미지를 흑백 이미지로 변환하여 영상 경계선 검출 후 Hough 변환을 통하여 영상 기울기를 검출하는 시스템을 고성능 DSP를 이용하여 구현하였다. 검출된 영상 기울기는 서보모터를 제어하여 카메라 지지대를 기울여도 카메라를 반대로 기울여 항상 기울어지지 않는 영상이 얻어지는 시스템을 구현 하였다.

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