• 제목/요약/키워드: Gradient search

검색결과 203건 처리시간 0.031초

HS 최적화 알고리즘을 이용한 계단응답과 연속시스템 인식 (Identification of Continuous System from Step Response using HS Optimization Algorithm)

  • 이태봉;손진근
    • 전기학회논문지P
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    • 제65권4호
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    • pp.292-297
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    • 2016
  • The first-order plus dead time(FOPDT) and second-order plus dead time(SOPDT), which describes a linear monotonic process quite well in most chemical and industrial processes and is often sufficient for PID and IMC controller tuning. This paper presents an application of heuristic harmony search(HS) optimization algorithm to the identification of linear continuous time-delay systems from step response. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. The effectiveness of the proposed identification method has been demonstrated through a number of simulation examples.

THE PERFORMANCE OF A MODIFIED ARMIJO LINE SEARCH RULE IN BFGS OPTIMIZATION METHOD

  • Kim, MinSu;Kwon, SunJoo;Oh, SeYoung
    • 충청수학회지
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    • 제21권1호
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    • pp.117-127
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    • 2008
  • The performance of a modified Armijo line search rule related to BFGS gradient type method with the results from other well-known line search rules are compared as well as analyzed. Although the modified Armijo rule does require as much computational cost as the other rules, it shows more efficient in finding local minima of unconstrained optimization problems. The sensitivity of the parameters used in the line search rules is also analyzed. The results obtained by implementing algorithms in Matlab for the test problems in [3] are presented.

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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.

무선 애드혹 네트워크를 위한 위치정보 기반 기울기 라우팅 알고리즘 (A Location Information-based Gradient Routing Algorithm for Wireless Ad Hoc Networks)

  • 방민영;이봉환
    • 정보처리학회논문지C
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    • 제17C권3호
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    • pp.259-270
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    • 2010
  • 본 논문에서는 무선 애드혹 네트워크에서 센서 노드들의 물리적 위치정보를 기반으로 라우팅 경로를 설정하기 위한 LIGR (Location Information-based Gradient Routing) 알고리즘을 제안한다. LIGR 알고리즘은 물리적 위치정보를 이용하여 소스 노드와 싱크 노드를 잇는 직선의 기울기를 통해 전송 방향과 탐색 범위를 결정함으로써 불필요한 데이터 전송과 경로 탐색 시간 및 전파 지연 시간을 감소시킨다. 또한 포워딩 노드 선택 시 배터리 부족 노드는 2순위 또는 3순위의 우선순위를 갖도록 하여 우선적으로 선택하지 않도록 함으로써 에너지 부족 노드가 네트워크상에서 라우터로서의 기능 수행보다는 데이터 수집을 위한 호스트로서의 기능을 수행하도록 하였다. LGR (Logical Grid Routing) 프로토콜에 비하여 LIGR 알고리즘은 평균 수신율, 평균 지연시간, 평균 잔여 에너지 및 네트워크 처리율에서 개선된 성능을 보였다.

가우시안 분포의 다중클래스 데이터에 대한 최적 피춰추출 방법 (Optimal feature extraction for normally distributed multicall data)

  • 최의선;이철희
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 추계종합학술대회 논문집
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    • pp.1263-1266
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    • 1998
  • In this paper, we propose an optimal feature extraction method for normally distributed multiclass data. We search the whole feature space to find a set of features that give the smallest classification error for the Gaussian ML classifier. Initially, we start with an arbitrary feature vector. Assuming that the feature vector is used for classification, we compute the classification error. Then we move the feature vector slightly and compute the classification error with this vector. Finally we update the feature vector such that the classification error decreases most rapidly. This procedure is done by taking gradient. Alternatively, the initial vector can be those found by conventional feature extraction algorithms. We propose two search methods, sequential search and global search. Experiment results show that the proposed method compares favorably with the conventional feature extraction methods.

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근사 선탐색을 이용한 동적 반응 최적화 (Dynamic response optmization using approximate search)

  • 김민수;최동훈
    • 대한기계학회논문집A
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    • 제22권4호
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    • pp.811-825
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    • 1998
  • An approximate line search is presented for dynamic response optimization with Augmented Lagrange Multiplier(ALM) method. This study empolys the approximate a augmented Lagrangian, which can improve the efficiency of the ALM method, while maintaining the global convergence of the ALM method. Although the approximate augmented Lagragian is composed of only the linearized cost and constraint functions, the quality of this approximation should be good since an approximate penalty term is found to have almost second-order accuracy near the optimum. Typical unconstrained optimization algorithms such as quasi-Newton and conjugate gradient methods are directly used to find exact search directions and a golden section method followed by a cubic polynomial approximation is empolyed for approximate line search since the approximate augmented Lagrangian is a nonlinear function of design variable vector. The numberical performance of the proposed approach is investigated by solving three typical dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested approach is robust and efficient.

Direct Search Methods for Nonlinear Optimization Problem used ART Theory

  • 손준혁;서보혁
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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    • pp.1830-1831
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    • 2006
  • In this paper, the search is conducted along each of the coordinate directions for finding the minimum. If $e_i$ is the unit vector along the coordinate direction i, we determine the value a, minimizing f(a)= $f(x+ae_i)$, where a is a real number. A move is made to the new point $x+a_ie_i$ at the end of the search along the direction i. In an n dimensional problem, we define the search along all the directions as one stage. The function value at the end of the stage is compared to the value at the beginning of the stage in establishing the convergence. The gradient appears to be zero at point. We can safeguard this by introducing an acceleration step of one additional step along the pattern direction developed by moves along the coordinate directions.

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Weight optimization of coupling with bolted rim using metaheuristics algorithms

  • Mubina Nancy;S. Elizabeth Amudhini Stephen
    • Coupled systems mechanics
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    • 제13권1호
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    • pp.1-19
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    • 2024
  • The effectiveness of coupling with a bolted rim is assessed in this research using a newly designed optimization algorithm. The current study, which is provided here, evaluates 10 contemporary metaheuristic approaches for enhancing the coupling with bolted rim design problem. The algorithms used are particle swarm optimization (PSO), crow search algorithm (CSA), enhanced honeybee mating optimization (EHBMO), Harmony search algorithm (HSA), Krill heard algorithm (KHA), Pattern search algorithm (PSA), Charged system search algorithm (CSSA), Salp swarm algorithm (SSA), Big bang big crunch optimization (B-BBBCO), Gradient based Algorithm (GBA). The contribution of the paper isto optimize the coupling with bolted rim problem by comparing these 10 algorithms and to find which algorithm gives the best optimized result. These algorithm's performance is evaluated statistically and subjectively.

Improved Gradient Direction Assisted Linking Algorithm for Linear Feature Extraction in High Resolution Satellite Images, an Iterative Dynamic Programming Approach

  • Yang, Kai;Liew, Soo Chin;Lee, Ken Yoong;Kwoh, Leong Keong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.408-410
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    • 2003
  • In this paper, an improved gradient direction assisted linking algorithm is proposed. This algorithm begins with initial seeds satisfying some local criteria. Then it will search along the direction provided by the initial point. A window will be generated in the gradient direction of the current point. Instead of the conventional method which only considers the value of the local salient structure, an improved mathematical model is proposed to describe the desired linear features. This model not only considers the value of the salient structure but also the direction of it. Furthermore, the linking problem under this model can be efficiently solved by dynamic programming method. This algorithm is tested for linear features detection in IKONOS images. The result demonstrates this algorithm is quite promising.

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Optimizations of Multi-hop Cooperative Molecular Communication in Cylindrical Anomalous-Diffusive Channel

  • Xuancheng Jin;Zhen Cheng;Zhian Ye;Weihua Gong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권4호
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    • pp.1075-1089
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    • 2024
  • In this paper, the optimizations of multi-hop cooperative molecular communication (CMC) system in cylindrical anomalous-diffusive channel in three-dimensional enviroment are investigated. First, we derive the performance of bit error probability (BEP) of CMC system under decode-and-forward relay strategy. Then for achieving minimum average BEP, the optimization variables are detection thresholds at cooperative nodes and destination node, and the corresponding optimization problem is formulated. Furthermore, we use conjugate gradient (CG) algorithm to solve this optimization problem to search optimal detection thresholds. The numerical results show the optimal detection thresholds can be obtained by CG algorithm, which has good convergence behaviors with fewer iterations to achieve minimized average BEP compared with gradient decent algorithm and Bisection method which are used in molecular communication.