• Title/Summary/Keyword: Information input algorithm

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Maximum Power Waveform Design for Bistatic MIMO Radar System

  • Shin, Hyuksoo;Yeo, Kwang-Goo;Yang, Hoongee;Chung, Youngseek;Kim, Jongman;Chung, Wonzoo
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.4
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    • pp.167-172
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    • 2014
  • In this paper we propose a waveform design algorithm that localizes the maximum output power in the target direction. We extend existing monostatic radar optimal waveform design schemes to bistatic multiple-input multiple-output (MIMO) radar systems. The algorithm simultaneously calculates the direction of departure (DoD) and the direction of arrival (DoA) using a two-dimensional multiple signal classification (MUSIC) method, and successfully localizes the maximum transmitted power to the target locations by exploiting the calculated DoD. The simulation results confirm the performance of the proposed algorithm.

Enhanced Prediction Algorithm for Near-lossless Image Compression with Low Complexity and Low Latency

  • Son, Ji Deok;Song, Byung Cheol
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.2
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    • pp.143-151
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    • 2016
  • This paper presents new prediction methods to improve compression performance of the so-called near-lossless RGB-domain image coder, which is designed to effectively decrease the memory bandwidth of a system-on-chip (SoC) for image processing. First, variable block size (VBS)-based intra prediction is employed to eliminate spatial redundancy for the green (G) component of an input image on a pixel-line basis. Second, inter-color prediction (ICP) using spectral correlation is performed to predict the R and B components from the previously reconstructed G-component image. Experimental results show that the proposed algorithm improves coding efficiency by up to 30% compared with an existing algorithm for natural images, and improves coding efficiency with low computational cost by about 50% for computer graphics (CG) images.

Machining Feature Recognition with Intersection Geometry between Design Primitives (설계 프리미티브 간의 교차형상을 통한 가공 피쳐 인식)

  • 정채봉;김재정
    • Korean Journal of Computational Design and Engineering
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    • v.4 no.1
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    • pp.43-51
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    • 1999
  • Producing the relevant information (features) from the CAD models of CAM, called feature recognition or extraction, is the essential stage for the integration of CAD and CAM. Most feature recognition methods, however, have problems in the recognition of intersecting features because they do not handle the intersection geometry properly. In this paper, we propose a machining feature recognition algorithm, which has a solid model consisting of orthogonal primitives as input. The algorithm calculates candidate features and constitutes the Intersection Geometry Matrix which is necessary to represent the spatial relation of candidate features. Finally, it recognizes machining features from the proposed candidate features dividing and growing systems using half space and Boolean operation. The algorithm has the following characteristics: Though the geometry of part is complex due to the intersections of design primitives, it can recognize the necessary machining features. In addition, it creates the Maximal Feature Volumes independent of the machining sequences at the feature recognition stage so that it can easily accommodate the change of decision criteria of machining orders.

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Face Tracking Using Skin-Color and Robust Hausdorff Distance in Video Sequences

  • Park, Jungho;Park, Changwoo;Park, Minyong
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.540-543
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    • 1999
  • We propose a face tracking algorithm using skin-color based segmentation and a robust Hausdorff distance. First, we present L*a*b* color model and face segmentation algorithm. A face is segmented from the first frame of input video sequences using skin-color map. Then, we obtain an initial face model with Laplacian operator. For tracking, a robust Hausdorff distance is computed and the best possible displacement t. is selected. Finally, the previous face model is updated using the displacement t. It is robust to some noises and outliers. We provide an example to illustrate the proposed tracking algorithm in video sequences obtained from CCD camera.

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Implementation of Real Time System for Personal Identification Algorithm Utilizing Hand Vein Pattern (정맥패턴을 이용한 개인식별 알고리즘의 고속 하드웨어 구현)

  • 홍동욱;임상균;최환수
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.560-563
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    • 1999
  • In this paper, we present an optimal hardware implementation for preprocessing of a person identification algorithm utilizing vein pattern of dorsal surface of hand. For the vein pattern recognition, the computational burden of the algorithm lies mainly in the preprocessing of the input images, especially in lowpass filtering. we could reduce the identification time to one tenth by hardware design of the lowpass filter compared to sequential computations. In terms of the computation accuracy, the simulation results show that the CSD code provided an optimized coefficient value with about 91.62% accuracy in comparison with the floating point implementation of current coefficient value of the lowpass filter. The post-simulation of a VHDL model has been performed by using the ModelSim$^{TM}$. The implemented chip operates at 20MHz and has the operational speed of 55.107㎳.㎳.

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An Efficient Incremental LR Parsing Algorithm (효율적인 점진적 LR 파성 알고리즘)

  • 안희학;유채우;송후봉
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.4
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    • pp.9-17
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    • 1994
  • The incremental parsing techniques are essential part of language-based environment which allow incremental construction of programs, as reparsing of modified part of the program alone enhances the system performance. A number of methods and algorithms have been proposed for incremental parsing and for the construction of incremental parsers. The purpose of this paper is to review the earlier incremental parsing algorithms which are too expensive in both time and space, and to present an efficient incremental LR parsing algorithm which is more efficient than the previous ones. In this paper, we generate automatically an extended LR parsing tables which allow the nonterminal symbols as well as terminal symbols for the input, and apply them to our efficient incremental LR parsing algorithm. Using these extended LR parsing tables. we suggest several methods to reduce its memory spaces and parsing steps as well. The algorithms described here were implemented in C language and YACC on a SUN UNIX OS, and were tested with several grammars and strings.

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An Image Data Compression Algorithm for a Home-Use Digital VCR Using SBC with Block-Adaptive Quantization (SBC와 블럭 적응 양자화를 이용한 가정용 디지탈 VCR 영상 압축 알고리듬)

  • 김주희;서정태;박용철;이제형;윤대희
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.9
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    • pp.124-132
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    • 1994
  • An image data compression method for a digital VCR must satisfy special requirements such as high speed playback. various edting capabilities and error concealment to provide immunity to tape dropouts. Taking these requirements requirements into consideration, this paper proposes a new interframe subband coding algorithm for a digital VCR. In the proposed method, continuous input images are fist partitioned into four frequency bands. The lowest frequency subband is coded with 3-D block adaptive quantization that removes the level redundancy within each level. The other higher frequency subbands are coded by an intraframe coding method using the property of the human visual system. To keep reasonable image quality in high speed palyback, a segment forming method in the frequency domaing is also proposed Computer simulation results demonstrate that the proposed algorithm has the potential of achieving virtually lossless compression in normal play and produces an image with less mosaic errors in high speed play.

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A Robust Model Reference Adaptive Control with a Modified $\sigma$-modification algorithm (새로운 $\sigma$-변형 알고리즘을 사용한 강인한 기준모델 적응제어)

  • 이호진;정종대;최계근
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.9
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    • pp.1322-1331
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    • 1989
  • This paper proposes a new adaptation algorithm with which a model reference adaptive control can give a local boundedness of the tracking error applied to a continuous-time linear time-invariant single-input single-output plant whose reduced-order model is of relative degree 1 and whose unmodeled dynamics may be represented in a sigular perturbation form. With the addition of an offset term and an extra adaptation structure, this algorithm is shown to have a robustness property in the sense that this gives zero residual tracking errors when the unmodeled dynamics are disappeared.

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Exact Histogram Specification Considering the Just Noticeable Difference

  • Jung, Seung-Won
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.2
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    • pp.52-58
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    • 2014
  • Exact histogram specification (EHS) transforms the histogram of an input image into the specified histogram. In the conventional EHS techniques, the pixels are first sorted according to their graylevels, and the pixels that have the same graylevel are further differentiated according to the local average of the pixel values and the edge strength. The strictly ordered pixels are then mapped to the desired histogram. However, since the conventional sorting method is inherently dependent on the initial graylevel-based sorting, the contrast enhancement capability of the conventional EHS algorithms is restricted. We propose a modified EHS algorithm considering the just noticeable difference. In the proposed algorithm, the edge pixels are pre-processed such that the output edge pixels obtained by the modified EHS can result in the local contrast enhancement. Moreover, we introduce a new sorting method for the pixels that have the same graylevel. Experimental results show that the proposed algorithm provides better image enhancement performance compared to the conventional EHS algorithms.

Optimization of Fed-Batch Yeast Culture by Using Genetic Algorithm (유전알고리즘을 이용한 유가식 효모 배양 최적화)

  • Na, Jeong-Geol;Jang, Yong-Geun;Jeong, Bong-Hyeon
    • KSBB Journal
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    • v.14 no.4
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    • pp.495-502
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    • 1999
  • The optimization of fed-batch yeast fermentation process has been performed using genetic algorithm(GA). Three strategies were designed and applied to obtain the optimal feed rate profiles. Genes in the chromosome (input variables for optimization) included feed rates on fixed time intervals (strategy I), or swiching times $t_s1\;and\;t_s2$, and feed rates on singular arc (strategy II), or feed rates and the length of time interval (strategy III). Strategy III showed the best results for all initial conditions due to efficient utilization of genetic information. Simulation results using GA showed similar or better performance compared with previous results by variational caculus and singular control approach.

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