• Title/Summary/Keyword: Information input algorithm

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3-D Object Tracking using 3-D Information and Optical Correlator in the Stereo Vision System (스테레오 비젼 시스템에서 3차원정보와 광 상관기를 이용한 3차원 물체추적 방법)

  • 서춘원;이승현;김은수
    • Journal of Broadcast Engineering
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    • v.7 no.3
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    • pp.248-261
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    • 2002
  • In this paper, we proposed a new 3-dimensional(3-D) object-tracking algorithm that can control a stereo camera using a variable window mask supported by which uses ,B-D information and an optical BPEJTC. Hence, three-dimensional information characteristics of a stereo vision system, distance information from the stereo camera to the tracking object. can be easily acquired through the elements of a stereo vision system. and with this information, we can extract an area of the tracking object by varying window masks. This extractive area of the tracking object is used as the next updated reference image. furthermore, by carrying out an optical BPEJTC between a reference image and a stereo input image the coordinates of the tracking objects location can be acquired, and with this value a 3-D object tracking can be accomplished through manipulation of the convergence angie and a pan/tilt of a stereo camera. From the experimental results, the proposed algorithm was found to be able to the execute 3-D object tracking by extracting the area of the target object from an input image that is independent of the background noise in the stereo input image. Moreover a possible implementation of a 3-D tele-working or an adaptive 3-D object tracker, using the proposed algorithm is suggested.

A study on the effectively optimized algorithm for an incremental attribute grammar (점진적 속성문법을 위한 효과적인 최적화 알고리즘에 관한 연구)

  • Jang, Jae-Chun;Ahn, Heui-Hak
    • The KIPS Transactions:PartA
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    • v.8A no.3
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    • pp.209-216
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    • 2001
  • The effective way to apply incremental attribute grammar to a complex language process is the use of optimized algorithm. In optimized algorithm for incremental attribute grammar, the new input attribute tree should be exactly compared with the previous input attribute tree, in order to determine which subtrees from the old should be used in constructing the new one. In this paper the new optimized algorithm was reconstructed by analyzing the algorithm suggested by Carle and Pollock, and a generation process of new attribute tree d’copy was added. Through the performance evaluation for the suggested matching algorithm, the run time is approximately improved by 19.5%, compared to the result of existing algorithm.

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A Design and Implementation of Real-time Video frame data Processing control for Block Matching Algorithm (고속블럭정합 알고리즘을 위한 실시간 영상프레임 데이터 처리 제어 방법의 설계 및 구현)

  • 이강환;황호정
    • Proceedings of the IEEK Conference
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    • 2001.06b
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    • pp.373-376
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    • 2001
  • This paper has been studied a real-time video frame data processing control that used the linear systolic array for motion estimation. The proposed data control processing provides to the input data into the multiple processor array unit(MPAU) from search area and reference block data. The proposed data control architecture has based on two slice band for input data processing. And it has no required external control logic blocks for input data as like reference block or search area data.

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Detection of False Laser Marks Using Neural Network (신경망을 이용한 레이저마크 오류 검출기법)

  • 신중돈;한헌수
    • Proceedings of the IEEK Conference
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    • 2002.06c
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    • pp.87-90
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    • 2002
  • This paper has been studied a new approach using neural network to detect false laser marks. In the proposed approach, input images are segmented into R, G and B colors and implements mask areas respectively. And then average and variation values of the each mask area are extracted for the learning process to minimize input nodes. Using this technique, the new input data is obtained and implemented to the back-propagation algorithm using multi layer perception. This paper reduces the computational complexity necessary and shows better effectiveness to inspect false laser marks.

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Input-output linearization of nonlinear systems via dynamic feedback (비선형 시스템의 동적 궤한 입출력 선형화)

  • 김용민;이홍기;전홍태
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.4
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    • pp.40-57
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    • 1998
  • The dynamic feedback is well-known to be much more powerful tool compensating the ononlinearity in nonlinear control system than the static one. In this paepr we consider the input-output linearization problem via a regular dynamic feedback which is to make linear the input-dependent part of the output sufficient conditions for the existence of such a regular dynamic feedback control law, after defining the structure algorithm for a dynamic feedback.

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Transistor Sizing Considering Slew Information to Reduce Glitch Power in CMOS Digital Circuit Design

  • Lee, Hyungwoo;Kim, Juho
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.1058-1061
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    • 2002
  • This paper presents the method of low power optimization considering the glitch reduction in CMOS circuits. Our algorithm utilizes the information of MOS size, the load capacitance of fan-out, and input slew to calculate the output waveform by using the linear signal model. Therefore, the accurate waveform of glitch can be obtained for estimation of power dissipation caused by glitches. Our algorithm is applied to ISCAS’85 benchmark circuits and experimental results show 23% glitch reduction and 11% total power reduction.

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A NOVEL UNSUPERVISED DECONVOLUTION NETWORK:EFFICIENT FOR A SPARSE SOURCE

  • Choi, Seung-Jin
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.336-338
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    • 1998
  • This paper presents a novel neural network structure to the blind deconvolution task where the input (source) to a system is not available and the source has any type of distribution including sparse distribution. We employ multiple sensors so that spatial information plays a important role. The resulting learning algorithm is linear so that it works for both sub-and super-Gaussian source. Moreover, we can successfully deconvolve the mixture of a sparse source, while most existing algorithms [5] have difficulties in this task. Computer simulations confirm the validity and high performance of the proposed algorithm.

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Sparsity Adaptive Expectation Maximization Algorithm for Estimating Channels in MIMO Cooperation systems

  • Zhang, Aihua;Yang, Shouyi;Li, Jianjun;Li, Chunlei;Liu, Zhoufeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.8
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    • pp.3498-3511
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    • 2016
  • We investigate the channel state information (CSI) in multi-input multi-output (MIMO) cooperative networks that employ the amplify-and-forward transmission scheme. Least squares and expectation conditional maximization have been proposed in the system. However, neither of these two approaches takes advantage of channel sparsity, and they cause estimation performance loss. Unlike linear channel estimation methods, several compressed channel estimation methods are proposed in this study to exploit the sparsity of the MIMO cooperative channels based on the theory of compressed sensing. First, the channel estimation problem is formulated as a compressed sensing problem by using sparse decomposition theory. Second, the lower bound is derived for the estimation, and the MIMO relay channel is reconstructed via compressive sampling matching pursuit algorithms. Finally, based on this model, we propose a novel algorithm so called sparsity adaptive expectation maximization (SAEM) by using Kalman filter and expectation maximization algorithm so that it can exploit channel sparsity alternatively and also track the true support set of time-varying channel. Kalman filter is used to provide soft information of transmitted signals to the EM-based algorithm. Various numerical simulation results indicate that the proposed sparse channel estimation technique outperforms the previous estimation schemes.

Hardware Implementation of the 3GPP KASUMI crypto algorithm

  • Kim, Ho-Won;Park, Yong-Je;Kim, Moo-Seop;Ryu, Hui-Su
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.317-320
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    • 2002
  • In this paper, we will present the design and implementation of the KASUMI crypto algorithm and confidentiality algorithm (f8) to an hardware chip for 3GPP system. The f8 algorithm is based on the KASUMI which is a block cipher that produces a 64-bit output from a 64-bit input under the control of a 128-bit key. Various architectures (low hardware complexity version and high performance version) of the KASUMI are made with a Xilinx FPGA and the characteristics such as hardware complexity and thor performance are analyzed.

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An Effective Cell Scheduling Algorithm for Input Queueing ATM Switch (입력단 큐잉 방식의 ATM 스위치를 위한 효율적 셀 중재 방식에 관한 연구)

  • 김용웅;원상연;박영근
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.1A
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    • pp.122-131
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    • 2000
  • In this paper, we propose a cell scheduling algorithm for input queueing ATM switch. The input queueing architecture is attractive for building an ultra-high speed ATM (Asynchronous Transfer Mode) switch. We proposea WMUCS (Weighted Matrix Unit Cell Scheduler) based on the MUCS which resolves HOL blocking and outputport contention. The MUCS algorithm selects an optimal set of entries as winning cells from traffic matrix (weightmatrix). Our WMUCS differs from the MUCS in generating weight matrices. This change solves the starvationproblem and it reduces the cell loss variance. The performance of the proposed algorithm is evaluated by thesimulation program written in C++. The simulation results show that the maximum throughput, the average celldelay, and the cell loss rate are significantly improved. We can see that the performance of WMUCS is excellentand the cost-effective implementation of the ATM switch using proposed cell scheduling algorithm.

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