• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3745-3761
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• 2020

Low-rank representation methods already achieve many applications in the image reconstruction. However, for high-gradient image patches with rich texture details and strong edge information, it is difficult to find sufficient similar patches. Existing low-rank representation methods usually destroy image critical details and fail to preserve edge structure. In order to promote the performance, a new representation-based image super-resolution reconstruction method is proposed, which combines gradient domain guided image filter with the structure-constrained low-rank representation so as to enhance image details as well as reveal the intrinsic structure of an input image. Firstly, we extract the gradient domain guided filter of each atom in high resolution dictionary in order to acquire high-frequency prior information. Secondly, this prior information is taken as a structure constraint and introduced into the low-rank representation framework to develop a new model so as to maintain the edges of reconstructed image. Thirdly, the approximate optimal solution of the model is solved through alternating direction method of multipliers. After that, experiments are performed and results show that the proposed algorithm has higher performances than conventional state-of-the-art algorithms in both quantitative and qualitative aspects.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.127-135
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• 2015

In this paper, we propose the semi-auto camera calibration method including user input. The proposed method estimates the vanishing points using user defined reference lines and defines the constraint for reducing outlier in vanishing points estimation process. The proposed camera calibration method based on both algebraic and geometric method improves a calibration performance for difficult condition, which represents that existing method can't calibrate a image. Experimental results show that the proposed method calibration accuracy higher than existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4738-4758
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• 2017

Resource allocation plays a crucial role in multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems to improve overall system performance. While previously proposed resource allocation algorithms are mainly designed from the point of view of the information-theoretic, we formulate the resource allocation problem as an average bit error rate (BER) minimization problem subject to a total power constraint when considering employing realistic MIMO detection techniques. Subsequently, we derive the optimal subcarrier and power allocation algorithms for three types of well-known MIMO detectors, including the maximum likelihood (ML) detector, linear detectors, and successive interference cancellation (SIC) detectors. To reduce the complexity, we also propose a two-step suboptimal algorithm that separates subcarrier and power allocation for each detector. We also analyze the diversity gain of the proposed suboptimal algorithms for various MIMO detectors. Simulation results confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity. Moreover, it is shown that the suboptimal algorithms perform better than the conventional algorithms that are known in the literature.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.4
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• pp.1023-1032
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• 1995

The multiple cooperating robot system plays an important role in the research of modern manufacturing system as the emphasis of production automation is more on the side of flexibility than before. While the kinematic and dynamic analysis of a single robot is performed as an open-loop chain, the dynamic formulation of robot in a multiple cooperating robot system differs from that of a single robot when the multiple cooperating robots form a closed kinematic chain holding an object simultaneously. The object may be any type from a rigid body to a multi-joint linkage. The mobility of the system depends on the kinematic configuration of the closed kinematic chain formed by robots and object, which also decides the number of independent input parameters. Since the mobility is not the same as the number of robot joints, proper constraint condition is sought. The constraints may be such that : the number of active robot joints is kept the same as mobility, all robot joints are active and have interrelations between each joint forces/torques, two robots have master-slave relation, or so on. The dynamic formulation of system is obtained. The formulation is based on recursive dual-number screw-calculus Newton-Eulerian approach which has been used for single robot analysis. This new scheme is recursive and compact symbolically and may facilitate the consideration of the object in real time.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10a
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• pp.124-140
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• 1995

The merit of fuzzy rule based systems stems from their capability of encoding qualitative knowledge of experts into quantitative rules. Recent advancement in automatic tuning or self-organization of fuzzy rules from experimental data further enhances their power, allowing the integration of the top-down encoding of knowledge with the bottom-up learning of rules. In this paper, methods of self-organizing fuzzy rules and of performing defuzzification and inference is presented based on a multi-resolution radial basis function network. The network learns an arbitrary input-output mapping from sample distribution as the union of hyper-ellipsoidal clusters of various locations, sizes and shapes. The hyper-ellipsoidal clusters, representing fuzzy rules, are self-organized based of global competition in such a way as to ensute uniform mapping errors. The cooperative interpolation among the multiple clusters associated with a mapping allows the network to perform a bidirectional many-to-many mapping, representing a particular from of defuzzification. Finally, an inference engine is constructed for the network to search for an optimal chain of rules or situation transitions under the constraint of transition feasibilities imposed by the learned mapping. Applications of the proposed network to skill acquisition are shown.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2616-2635
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• 2013

In this paper, we propose an iterative transceiver design in a multi-relay multi-user multiple-input multiple-output (MIMO) system. The design criterion is to minimize sum mean squared error (SMSE) under relay sum power constraint (RSPC) where only local channel state information (CSI)s are available at relays. Local CSI at a relay is defined as the CSI of the channel between BS and the relay in the $1^{st}$ hop link, and the CSI of the channel between the relay and all users in the $2^{nd}$ hop link. Exploiting BS transmitter structure which is concatenated with block diagonalization (BD) precoder, each relay's precoder can be determined using local CSI at the relay. The proposed scheme is based on sequential iteration of two stages; stage 1 determines BS transmitter and relay precoders jointly with SMSE duality, and stage 2 determines user receivers. We verify that the proposed scheme outperforms simple amplify-and-forward (SAF), minimum mean squared error (MMSE) relay, and an existing good scheme of [13] in terms of both SMSE and sum-rate performances.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.141-149
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• 2010

This paper contains impulsive maneuver which considers fuel consumption balance of chief satellite and deputy satellite in satellite formation flying. Thrust input is obtained by Lagrange' Multiplier method which is constructed by cost function with weight parameter of each satellite. Energy matching constraint is applied for boundedness of relative orbit, and theoretical solutions are verified by simulation results. Simulations are divided into two scenarios, with or without air-drag effect. This paper's results are expected to be used in real satellite formation flying, when fuel-balancing impulsive maneuver for relative orbit boundedness is needed.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.290-293
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• 2011

현재 전국적으로 도시 철도의 각 호선별 열차 운행은 차량기지에서 출고된 열차가 기점과 종점의 두 지점 사이를 여러 차례 왕복한 후 정해진 차량기지로 입고방식을 취하는 것이 대부분이다. 그리고 매일 열차 운행이 개시되기 전 각 차량기지의 보유 열차 수는 전날과 동일해야 하는데 차량 기지가 복수로 존재할 경우 열차 운행계획 수립 시 어느 기지에서 출고한 어떤 차량이 어느 기지로 입고해야 하는지를 결정하는 문제가 더욱 어려워진다. 승객 수송을 위한 여러 가지 요구조건 또한 모두 만족시키면서 이 입출고 제약도 만족시키는 것은 쉬운 문제가 아니다. 하지만 열차 운행 계획 수립을 자동으로 생성하는 방법에 대한 연구는 매우 부족한 실정이다. 따라서 본 논문에서는 차량기지가 복수로 존재하는 상황에서의 현실 제약을 모두 만족하는 도시철도 운행 계획을 자동으로 생성하는 방법을 제시한다. 본 논문에서 제시하는 방법으로 실험 한 결과 기존의 방법으로 해결이 어려운 차량기지가 복수로 존재하는 상황에서의 현실제약을 모두 만족하는 계획을 빠른 시간 내에 수립 할 수 있음을 확인 하였다.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1680-1691
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• 2004

One of the representative methods of optical flow is a gradient method which estimates the movement of an object based on the differential of image brightness. However, the method is ineffective for large displacement of the object and many improved methods have been proposed to copy with such limitations. One of these improved techniques is the multigrid processing, which is used in many optical flow algorithms. As an alternative novel technique we have been proposing an orthogonal functional expansion method, where whole displacements are expanded from low frequency terms. This method is expected to be applicable to flow estimation with large displacement and deformation including expansion and contraction, which are difficult to cope with by conventional optical flow methods. In the orthogonal functional expansion method, the apparent displacement field is calculated iteratively by a projection method which utilizes derivatives of the invariant constraint equations of brightness constancy. One feature of this method is that differentiation of the input image is not necessary, thereby reducing sensitivity to noise. In this paper, we apply our method to several real images in which the objects undergo large displacement and/or deformation including expansion. We demonstrate the effectiveness of the orthogonal functional expansion method by comparing with conventional methods including our optimally scaled multigrid optical flow algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.6
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• pp.535-544
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• 2013

This paper considers an uplink power control scheme for a virtual multi-input multi-output (MIMO) multi-cell system where multiple mobile stations with single transmit antenna form a virtual MIMO link. Unlike the conventional approach of the game theoretic formulation to add a power penalty term to improve the performance, a constraint on the total effective interference power is introduced to the maximization of the utility function of the transmission rate with linear receive beamforming. Introducing inertia, we show that the proposed power control is guaranteed to converge. The simulation results verify that the proposed power allocation can significantly improve the performance in an interference limited multi-cell system.