• Title/Summary/Keyword: vector computer

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A Computationally Efficient Sphere Decoding Algorithm with Smart Radius Control (스마트 반지름 제어를 사용한 효율적인 구복호 알고리즘)

  • Han, Hee-Goo;Oh, Seong-Keun
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.93-96
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    • 2005
  • We propose a computationally efficient sphere decoding (SD) algorithm with smart radius control (SRC). As a baseline algorithm for SD, we consider the modified Schnorr-Euchner (SE) algorithm [1] (hereafter, called as the MSE algorithm). In principle, the radius after zero-forcing decision feedback equalization (ZF-DFE) estimation can be reduced further if we select a new lattice vector closer to the received signal vector than the lattice vector corresponding to the ZF-DFE estimate does. In our case, we obtain such a better lattice vector by performing a sequence of alternating one-dimensional searches, starting from the ZF-DFE estimate. We then develop a novel SRC algorithm that adopts adaptively the additional radius reduction process according to the estimated signal-to-noise-power ratio (SNR) after ZF-DFE estimation. In addition, we analyze the effect of detection ordering on the complexity for SD. Column-norm ordering of the channel matrix and optimal ordering [1] are considered here. From our analyses, we see that SRC can reduce greatly the complexity for SD and the degree of complexity reduction gets significant as the SNR decreases, irrespective of detection ordering schemes used.

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A Distance Approach for Open Information Extraction Based on Word Vector

  • Liu, Peiqian;Wang, Xiaojie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.6
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    • pp.2470-2491
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    • 2018
  • Web-scale open information extraction (Open IE) plays an important role in NLP tasks like acquiring common-sense knowledge, learning selectional preferences and automatic text understanding. A large number of Open IE approaches have been proposed in the last decade, and the majority of these approaches are based on supervised learning or dependency parsing. In this paper, we present a novel method for web scale open information extraction, which employs cosine distance based on Google word vector as the confidence score of the extraction. The proposed method is a purely unsupervised learning algorithm without requiring any hand-labeled training data or dependency parse features. We also present the mathematically rigorous proof for the new method with Bayes Inference and Artificial Neural Network theory. It turns out that the proposed algorithm is equivalent to Maximum Likelihood Estimation of the joint probability distribution over the elements of the candidate extraction. The proof itself also theoretically suggests a typical usage of word vector for other NLP tasks. Experiments show that the distance-based method leads to further improvements over the newly presented Open IE systems on three benchmark datasets, in terms of effectiveness and efficiency.

Sensorless vector control for super-high speed PMSM drive

  • Bae Bon-Ho;Sul Seung-Ki;Kwon Jeong-Hyeck;Shin Jong-Sub
    • Proceedings of the KIPE Conference
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    • 2001.10a
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    • pp.773-778
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    • 2001
  • This paper describes the implementation of the vector control schemes for a variable-speed 131kW PMSM (Permanent Magnet Synchronous Motor) in super-high speed application. The vector control with synchronous reference frame current regulator has been implemented with the challenging requirements such as the extremely low stator inductance$(28^{\mu}H)$, the high dc link voltage(600V) and the high excitation frequency(1.2kHz). Because the conventional position sensor is not reliable in super-high speed, a vector control scheme without any position sensor has been proposed. The proposed sensorless algorithm is implemented by processing the output voltage of the PI current regulator, and hence the structure is simple and the estimated speed is robust to the measurement noise. The experimental system has been built and the proposed control has been implemented and evaluated. The test result, up to the speed of 60,000 r/min, shows the validity of the proposed control.

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A Scene Change Detection using Motion Estimation in Animation Sequence (움직임 추정을 이용한 애니메이션 영상의 장면전환 검출)

  • Kwak, Sung-Keun
    • Journal of the Korea Computer Industry Society
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    • v.9 no.4
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    • pp.149-156
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    • 2008
  • There is the temporal correlation of a animation sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the scene change detection algorithm for block matching using the temporal correlation of the animation sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that the proposed algorithm has better detection performance, such as recall rate, then the existing method. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

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Frame Rate Up-Conversion Considering The Direction and Magnitude of Identical Motion Vectors (동일한 움직임 벡터들의 방향과 크기를 고려한 프레임율 증가기법)

  • Park, Jonggeun;Jeong, Jechang
    • Journal of Broadcast Engineering
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    • v.20 no.6
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    • pp.880-887
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    • 2015
  • In this paper, frame rate up conversion (FRUC) algorithm considering the direction and magnitude of identical motion vectors is proposed. extended bilateral motion estimation (EBME) has higher complexity than bilateral motion estimation (BME). By using average magnitude of motion vector with x and y direction respectively, dynamic frame and static frame are decided. We reduce complexity to decide EBME. also, After we compare the direction and magnitude of identical motion vectors, We reduce complexity to decide motion vector smoothing(MVS). Experimental results show that this proposed algorithm has fast computation and better peak singnal to noise ratio(PSNR) results compared with EBME.

Low-power Frequency Offset Synchronization for IEEE 802.11a Using CORDIC Algorithm (CORDIC을 이용한 IEEE 802.11a용 저전력 주파수 옵셋 동기화기)

  • Jang, Young-Beom;Han, Jae-Woong;Hong, Dae-Ki
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.46 no.2
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    • pp.66-72
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    • 2009
  • In this paper, an efficient frequency offset synchronization structure for OFDM(Orthogonal Frequency Division Multiplexing) is proposed. Conventional CORDIC(Coordinate Rotation Digital Computer) algorithm for frequency offset synchronization utilizes two CORDIC hardware i.e., one is vector mode for phase estimation, the other is rotation mode for compensation. But proposed structure utilizes one CORDIC hardware and divider. Through simulation, it is shown that hardware implementation complexity is reduced compared with conventional structures. The Verilog-HDL coding and front-end chip implementation results for the proposed structure show 22.1% gate count reduction comparison with those of the conventional structure.

Design and Implementation of OFDM Frequency Offset Synchronization Block Using CORDIC (CORDIC을 이용한 OFDM 주파수 옵셋 동기부 설계 및 구현)

  • Jang, Young-Beom;Han, Jae-Woong;Hong, Dae-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.5
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    • pp.118-125
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    • 2008
  • In this paper, an efficient frequency offset synchronization structure for OFDM(Orthogonal Frequency Division Multiplexing) is proposed. Conventional CORDIC(Coordinate Rotation Digital Computer) algorithm for frequency offset synchronization utilizes two CORDIC hardware i.e., one is vector mode for phase estimation, the other is rotation mode for compensation. But proposed structure utilizes one CORDIC hardware and divider. Through simulation, it is shown that hardware implementation complexity is reduced compared with conventional structures. The Verilog-HDL coding and front-end chip implementation results for the proposed structure show 22.1% gate count reduction comparison with those of the conventional structure.

Video Indexing using Motion vector and brightness features (움직임 벡터와 빛의 특징을 이용한 비디오 인덱스)

  • 이재현;조진선
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.4
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    • pp.27-34
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    • 1998
  • In this paper we present a method for automatic motion vector and brightness based video indexing and retrieval. We extract a representational frame from each shot and compute some motion vector and brightness based features. For each R-frame we compute the optical flow field; motion vector features are then derived from this flow field, BMA(block matching algorithm) is used to find motion vectors and Brightness features are related to the cut detection of method brightness histogram. A video database provided contents based access to video. This is achieved by organizing or indexing video data based on some set of features. In this paper the index of features is based on a B+ search tree. It consists of internal and leaf nodes stores in a direct access a storage device. This paper defines the problem of video indexing based on video data models.

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Study on Algorithms of Mobile Vector Map Generalization Operators for Location Information Search (위치 정보 검색을 위한 모바일 벡터 지도 일반화 연산 알고리즘 연구)

  • Kim, Hyun-Woo;Choi, Jin-Oh
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.167-170
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    • 2005
  • In the mobile environments for the vector map services, a map simplification work through the map generalization steps helps improve the readability of the map on a large scale. The generalization operations are various such as selection, aggregation, simplification, displacement, and so on, the formal operation algorithms have not been built yet. Because the algorithms require deep special knowledge and heuristic, which make it hard to automate the processes. This thesis proposes some map generalization algorithms specialized in mobile vector map services, based on previous works. We will show the detail to adapt the approaches on the mobile environment, to display complex spatial objects efficiently on the mobile devices which have restriction on the resources

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Motion Vector Resolution Decision Algorithm based on Neural Network for Fast VVC Encoding (고속 VVC 부호화를 위한 신경망 기반 움직임 벡터 해상도 결정 알고리즘)

  • Baek, Han-gyul;Park, Sang-hyo
    • Journal of Broadcast Engineering
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    • v.26 no.5
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    • pp.652-655
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    • 2021
  • Among various inter prediction techniques of Versatile Video Coding (VVC), adaptive motion vector resolution (AMVR) technology has been adopted. However, for AMVR, various MVs should be tested per each coding unit, which needs a computation of rate-distortion cost and results in an increase in encoding complexity. Therefore, in order to reduce the encoding complexity of AMVR, it is necessary to effectively find an optimal AMVR mode. In this paper, we propose a lightweight neural network-based AMVR decision algorithm based on more diverse datasets.