• Title/Summary/Keyword: gradient algorithm

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

  • Lee, Seung-Joon;Rhee, Sang-Burm
    • Journal of the Korea Computer Industry Society
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    • v.9 no.3
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    • pp.129-136
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    • 2008
  • This paper implement image gradient detection algorithm with high-performance DSP. First the NTSC color image convert to B/W image. The image gradient detect with Hough transform after edge detection image from the B/W images. The value of image gradient detection control the servo motor to original position of the NTSC camera if camera base to the left or right tilt.

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DNA computing using a difference of melting temperature among DNA fragments

  • Lee, Ji-Yeon;Sin, Su-Yong;Jang, Byeong-Tak;Park, Tae-Hyeon
    • 한국생물공학회:학술대회논문집
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    • 2002.04a
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    • pp.539-542
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    • 2002
  • We propose new encoding method for numerical data in DNA using temperature gradient. To represent numerical values in DNA sequences, we introduce melting temperature. Since DNA strands representing smaller values have a lower Tm, they tend to denature with ease and also easily amplified by denaturation temperature gradient PCR. We also implement a local search molecular algorithm using temperature gradient, which is contrasted to conventional exhaustive search molecular algorithms. The proposed methods are verified by solving an instance of the travelling salesman problem. We could effectively amplify the correct solutions and the use of temperature gradient made the detection of solutions easier.

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Economic Dispatch of Thermal Units of a GENCO Using the Gradient Projection Method (경사 투영법을 이용한 발전사업자의 경제급전)

  • 정정원
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.52 no.9
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    • pp.550-556
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    • 2003
  • Price-based unit commitment is one of bidding strategies which a Genco may take in a practical manner. For that purpose, it is required for a Genco to decide output levels of its generators at each trade period. In this paper, an economic dispatch of thermal units is proposed considering the quantity of reserve contracts. A gradient projection algorithm is adopted as an optimization tool. A direct form of a projection matrix without any calculation of matrix inverse and multiplications is induced. Besides, it is proved that there is no need to check one of the two optimality conditions in the gradient projection method, which also requires matrix inverse and multiplications.

Induced Charge Distribution Using Accelerated Uzawa Method (가속 Uzawa 방법을 이용한 유도전하계산법)

  • Kim, Jae-Hyun;Jo, Gwanghyun;Ha, Youn Doh
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.4
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    • pp.191-197
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    • 2021
  • To calculate the induced charge of atoms in molecular dynamics, linear equations for the induced charges need to be solved. As induced charges are determined at each time step, the process involves considerable computational costs. Hence, an efficient method for calculating the induced charge distribution is required when analyzing large systems. This paper introduces the Uzawa method for solving saddle point problems, which occur in linear systems, for the solution of the Lagrange equation with constraints. We apply the accelerated Uzawa algorithm, which reduces computational costs noticeably using the Schur complement and preconditioned conjugate gradient methods, in order to overcome the drawback of the Uzawa parameter, which affects the convergence speed, and increase the efficiency of the matrix operation. Numerical models of molecular dynamics in which two gold nanoparticles are placed under external electric fields reveal that the proposed method provides improved results in terms of both convergence and efficiency. The computational cost was reduced by approximately 1/10 compared to that for the Gaussian elimination method, and fast convergence of the conjugate gradient, as compared to the basic Uzawa method, was verified.

A Study for Individual Identification by Discriminating the Finger Face Image (손가락 면 영상 판별에 의한 개인 식별 연구)

  • Kim, Hee-Sung;Bae, Byung-Kyu
    • Journal of Korea Multimedia Society
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    • v.13 no.3
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    • pp.378-391
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    • 2010
  • In this paper, it is tested that an individual is able to be identified with finger face images and the results are presented. Special operators, FFG(Facet Function Gradient) masks by which the gradient of a facet function fit on a gray levels of image patches can be computed are used and a new procedure named F-algorithm is introduced to match the finger face images. The finger face image is divided into the equal subregions and each subregions are divided into equal patches with this algorithm. The FFG masks are used for convolution operation over each patch to produce scalar values. These values from a feature matrix, and the identity of fingers is determined by a norm of the elements of the feature matrices. The distribution of the norms shows conspicuous differences between the pairs of hand images of the same persons and the pairs of the different persons. This is a result to prove the ability of discrimination with the finger face image. An identification rate of 95.0% is obtained as a result of the test in which 500 hand images taken from 100 persons are processed through F-algorithm. It is affirmed that the finger face reveals to be such a good biometrics as other hand parts owing to the ability of discrimination and the identification rate.

Statistical Estimation and Algorithm in Nonlinear Functions

  • Jea-Young Lee
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.135-145
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    • 1995
  • A new algorithm was given to successively fit the multiexponential function/nonlinear function to data by a weighted least squares method, using Gauss-Newton, Marquardt, gradient and DUD methods for convergence. This study also considers the problem of linear-nonlimear weighted least squares estimation which is based upon the usual Taylor's formula process.

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Low Complexity Gradient Magnitude Calculator Hardware Architecture Using Characteristic Analysis of Projection Vector and Hardware Resource Sharing (정사영 벡터의 특징 분석 및 하드웨어 자원 공유기법을 이용한 저면적 Gradient Magnitude 연산 하드웨어 구현)

  • Kim, WooSuk;Lee, Juseong;An, Ho-Myoung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.4
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    • pp.414-418
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    • 2016
  • In this paper, a hardware architecture of low area gradient magnitude calculator is proposed. For the hardware complexity reduction, the characteristic of orthogonal projection vector and hardware resource sharing technique are applied. The proposed hardware architecture can be implemented without degradation of the gradient magnitude data quality since the proposed hardware is implemented with original algorithm. The FPGA implementation result shows the 15% of logic elements and 38% embedded multiplier savings compared with previous work using Altera Cyclone VI (EP4CE115F29C7N) FPGA and Quartus II v15.0 environment.

A Parallel Algorithm for Large DOF Structural Analysis Problems (대규모 자유도 문제의 구조해석을 위한 병렬 알고리즘)

  • Kim, Min-Seok;Lee, Jee-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.23 no.5
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    • pp.475-482
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    • 2010
  • In this paper, an efficient two-level parallel domain decomposition algorithm is suggested to solve large-DOF structural problems. Each subdomain is composed of the coarse problem and local problem. In the coarse problem, displacements at coarse nodes are computed by the iterative method that does not need to assemble a stiffness matrix for the whole coarse problem. Then displacements at local nodes are computed by Multi-Frontal Sparse Solver. A parallel version of PCG(Preconditioned Conjugate Gradient Method) is developed to solve the coarse problem iteratively, which minimizes the data communication amount between processors to increase the possible problem DOF size while maintaining the computational efficiency. The test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF structural problems.

An Adaptive Gradient-Projection Image Restoration using Spatial Local Constraints and Estimated Noise (국부 공간 제약 정보 및 예측 노이즈 특성을 이용한 적응 Gradient-Projection 영상 복원 방식)

  • Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.10C
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    • pp.975-981
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    • 2007
  • In this paper, we propose a spatially adaptive image restoration algorithm using local and statistics and estimated noise. The ratio of local mean, variance, and maximum values with different window size is used to constrain the solution space, and these parameters are computed at each iteration step using partially restored image. In addition, the additive noise estimated from partially restored image and the local constraints are used to determine a parameter for controlling the degree of local smoothness on the solution. The resulting iterative algorithm exhibits increased convergence speed when compared to the non-adaptive algorithm. In addition, a smooth solution with a controlled degree of smoothness is obtained without a prior knowledge about the noise. Experimental results demonstrate that the proposed algorithm requires the similar iteration number to converge, but there is the improvement of SNR more than 0.2 dB comparing to the previous approach.

Pedestrian Recognition using Adaboost Algorithm based on Cascade Method by Curvature and HOG (곡률과 HOG에 의한 연속 방법에 기반한 아다부스트 알고리즘을 이용한 보행자 인식)

  • Lee, Yeung-Hak;Ko, Joo-Young;Suk, Jung-Hee;Roh, Tae-Moon;Shim, Jae-Chang
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.6
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    • pp.654-662
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    • 2010
  • In this paper, we suggest an advanced algorithm, to recognize pedestrian/non-pedestrian using second-stage cascade method, which applies Adaboost algorithm to make a strong classification from weak classifications. First, we extract two feature vectors: (i) Histogram of Oriented Gradient (HOG) which includes gradient information and differential magnitude; (ii) Curvature-HOG which is based on four different curvature features per pixel. And then, a strong classification needs to be obtained from weak classifications for composite recognition method using both HOG and curvature-HOG. In the proposed method, we use one feature vector and one strong classification for the first stage of recognition. For the recognition-failed image, the other feature and strong classification will be used for the second stage of recognition. Based on our experiment, the proposed algorithm shows higher recognition rate compared to the traditional method.