• 제목/요약/키워드: iterative sequence

검색결과 148건 처리시간 0.03초

Algorithmic Properties of Isotone Complementarity Problems

  • Ahn, Byong-Hun
    • 한국경영과학회지
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    • 제12권1호
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    • pp.10-18
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    • 1987
  • This paper discusses algorithmic properties of a class of complementarity programs involving strictly diagonally isotone and off-diagonally isotone functions, i. e., functions whose Jacobian matrices have positive diagonal elements and nonnegative off-diagonal elements, A typical traffic equilibrium under elastic demands is cast into this class. Algorithmic properties of these complementarity problems, when a Jacobi-type iteration is applied, are investigated. It is shown that with a properly chosen starting point the generated sequence are decomposed into two converging monotonic subsequences. This and related will be useful in developing solution procedures for this class of complementarity problems.

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A NOTE ON GREEDY ALGORITHM

  • Hahm, Nahm-Woo;Hong, Bum-Il
    • 대한수학회보
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    • 제38권2호
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    • pp.293-302
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    • 2001
  • We improve the greedy algorithm which is one of the general convergence criterion for certain iterative sequence in a given space by building a constructive greedy algorithm on a normed linear space using an arithmetic average of elements. We also show the degree of approximation order is still $Ο(1\sqrt{\n}$) by a bounded linear functional defined on a bounded subset of a normed linear space which offers a good approximation method for neural networks.

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A MODIFIED PROXIMAL POINT ALGORITHM FOR SOLVING A CLASS OF VARIATIONAL INCLUSIONS IN BANACH SPACES

  • LIU, YING
    • Journal of applied mathematics & informatics
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    • 제33권3_4호
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    • pp.401-415
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    • 2015
  • In this paper, we propose a modified proximal point algorithm which consists of a resolvent operator technique step followed by a generalized projection onto a moving half-space for approximating a solution of a variational inclusion involving a maximal monotone mapping and a monotone, bounded and continuous operator in Banach spaces. The weak convergence of the iterative sequence generated by the algorithm is also proved.

쿼드트리로 표현된 한글 문서 영상에서의 문자 추출 (Character Extraction from the Hangeul Document Image Represented by a Quadtree)

  • 백은경;조동섭
    • 대한전기학회논문지
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    • 제41권7호
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    • pp.793-801
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    • 1992
  • This paper proposes a method of extracting connected strokes and characters in a Hangeul document image represented by a quadtree. Connected strokes are extracted by examining adjacency for each node of a black region to the side of east and south. Then, each character is extracted by the sizes and the relations of connected strokes. This is done by iterative vertical and horizontal manipulation. The result shows all characters are extracted in the same sequence as that of context with space and time efficiency.

Distortion Variation Minimization in low-bit-rate Video Communication

  • Park, Sang-Hyun
    • Journal of information and communication convergence engineering
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    • 제5권1호
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    • pp.54-58
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    • 2007
  • A real-time frame-layer rate control algorithm with a token bucket traffic shaper is proposed for distortion variation minimization. The proposed rate control method uses a non-iterative optimization method for low computational complexity, and performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. The proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performances than the existing rate control method.

영상합성을 위한 영상으로부터의 견실한 카메라피라미터 확정법 (Robust Estimation of Camera Parameters from Video Signals for Video Composition)

  • 박종일;이충웅
    • 전자공학회논문지B
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    • 제32B권10호
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    • pp.1305-1313
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    • 1995
  • In this paper, we propose a robust estimation of camera parameters from image sequence for high quality video composition. We first establish correspondence of feature points between consecutive image fields. After the establishment, we formulate a nonlinear least-square data fitting problem. When the image sequence contains moving objects, and/or when the correspondence establishment is not successful for some feature points, we get bad observations, outliers. They should be properly eliminated for a good estimation. Thus, we propose an iterative algorithm for rejecting the outliers and fitting the camera parameters alternatively. We show the validity of the proposed method using computer generated data sets and real image sequeces.

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An online Calibration Algorithm using binary spreading code for the CDMA-based Adaptive Antenna Array

  • Lee, Chong-Hyun
    • 조명전기설비학회논문지
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    • 제20권9호
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    • pp.32-39
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    • 2006
  • In this paper, an iterative subspace-based calibration algorithm for a CDMA-based antenna array in the presence of unknown gain and phase error is presented. The algorithm does not depend on the array geometry and does not require a prior knowledge of the Directions Of Arrival (DOA) of the signals. The method requires the code sequence of a reference user only. The proposed algorithm is based on the subspace method and root finding approach, and it provides estimates of the calibration vector, the DOA and the channel impulse response, by using the code sequence of a reference user. The performance of the proposed algorithm was investigated by means of computer simulations and was verified using field data measured through a custom-built W-CDMA test-bed. The data show that experimental results match well with the theoretical calibration algorithm. Also, teh study propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the requirement of initial guessing in the subspace-based approach.

Doubly-Selective Channel Estimation for OFDM Systems Using a Pilot-Embedded Training Scheme

  • Wang, Li-Dong;Lim, Dong-Min
    • Journal of electromagnetic engineering and science
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    • 제6권4호
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    • pp.203-208
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    • 2006
  • Channel estimation and data detection for OFDM systems over time- and frequency-selective channels are investigated. Relying on the complex exponential basis expansion channel model, a pilot-embedded channel estimation scheme with low computational complexity and spectral efficiency is proposed. A periodic pilot sequence is superimposed at a low power on information bearing sequence at the transmitter before modulation and transmission. The channel state information(CSI) can be estimated using the first-order statistics of the received data. In order to enhance the performance of channel estimation, we recover the transmitted data which can be exploited to estimate CSI iteratively. Simulation results show that the proposed method is suitable for doubly-selective channel estimation for the OFDM systems and the performance of the proposed method can be better than that of the Wiener filter method under some conditions. Through simulations, we also analyze the factors which can affect the system performances.

STRONG CONVERGENCE THEOREMS FOR NONEXPANSIVE MAPPINGS AND INVERSE-STRONGLY-MONOTONE MAPPINGS IN A BANACH SPACE

  • Liu, Ying
    • East Asian mathematical journal
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    • 제26권5호
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    • pp.627-639
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    • 2010
  • In this paper, we introduce a new iterative sequence finding a common element of the set of fixed points of a nonexpansive mapping and the set of solutions of the variational inequality for an inverse-strongly-monotone mapping in a Banach space. Then we show that the sequence converges strongly to a common element of two sets. Using this result, we consider the problem of finding a common element of the set of fixed points of a nonexpansive mapping and the set of zeros of an inverse-strongly-monotone mapping, the fixed point problem and the classical variational inequality problem. Our results improve and extend the corresponding results announced by many others.

Scale Invariant Auto-context for Object Segmentation and Labeling

  • Ji, Hongwei;He, Jiangping;Yang, Xin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권8호
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    • pp.2881-2894
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    • 2014
  • In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.