• Title/Summary/Keyword: minimum Euclidean distance

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AN UPPER BOUND ON THE NUMBER OF PARITY CHECKS FOR BURST ERROR DETECTION AND CORRECTION IN EUCLIDEAN CODES

  • Jain, Sapna;Lee, Ki-Suk
    • Journal of the Korean Mathematical Society
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    • v.46 no.5
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    • pp.967-977
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    • 2009
  • There are three standard weight functions on a linear code viz. Hamming weight, Lee weight, and Euclidean weight. Euclidean weight function is useful in connection with the lattice constructions [2] where the minimum norm of vectors in the lattice is related to the minimum Euclidean weight of the code. In this paper, we obtain an upper bound over the number of parity check digits for Euclidean weight codes detecting and correcting burst errors.

Optimum Convolutional Error Correction Codes for FQPSK-B Signals

  • Park, Hyung-Chul
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.5C
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    • pp.611-617
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    • 2004
  • The optimum convolutional error correction codes for recently standardized Feher-patented quadrature phase-shift keying (FQPSK-B) modulation are proposed. We utilize the continuous phase modulation characteristics of FQPSK-B signals for calculating the minimum Euclidean distance of convolutional coded FQPSK-B signal. It is shown that the Euclidean distance between two FQPSK-B signals is proportional to the Hamming distance between two binary data sequence. Utilizing this characteristic, we show that the convolutional codes with optimum free Hamming distance is the optimum convolutional codes for FQPSK-B signals.

Efficient Similarity Search in Time Series Databases Based on the Minimum Distance (최단거리에 기반한 시계열 데이타의 효율적인 유사 검색)

  • 이상준;권동섭;이석호
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.04a
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    • pp.533-535
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    • 2003
  • The Euclidean distance is sensitive to the absolute offsets of time sequences, so it is not a suitable similarity measure in terms of shape. In this paper. we propose an indexing scheme for efficient matching and retrieval of time sequences based on the minimum distance. The minimum distance can give a better estimation of similarity in shape between two time sequences. Our indexing scheme can match time sequences of similar shapes irrespective of their vortical positions and guarantees no false dismissals

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Performance Enhancement of Trellis Coded Mary PSK using Minimum Hamming Distance (최소해밍거리를 이용한 트렐리스 부호화된 M- ray PSK의 성능 향상)

  • 은도현;조훈상;이순흠
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.12 no.3
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    • pp.417-424
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    • 2001
  • This paper proposes new symbol mapping method that can enhance the performance of trellis coded M-ary PSK compared with conventional symbol mapping methods in AWGN environment. Since the basic criteria of TCM design is Maximum Euclidean distance in AWGN, conventional symbol mapping method keep this basic criteria. In this paper, proposed new symbol mapping method uses both Euclidean distance and Hamming distance to design, while conventional methods make use of only optimal Euclidean distance. New symbol mapping method show the better BER performance than the other through computer simulation and error equations.

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An Efficient Method for Minimum Distance Problem Between Shapes Composed of Circular Arcs and Lines (원호와직선으로 구성된 도형간의 효율적인 최소거리 계산방법)

  • 김종민;김민환
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.43 no.5
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    • pp.848-860
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    • 1994
  • Generally, to get the minimum distance between two arbitrary shapes that are composed of circular arcs and lines, we must calculate distances for all the possible pairs of the components from two given shapes. In this paper, we propose an efficient method for the minimum distance problem between two shapes by using their structural features after extracting the reduced component lists which are essential to calculate the minimum distance considering the relationship of shape location. Even though the reduced component lists may contain all the components of the shapes in the worst case, in the average we can reduce the required computation much by using the reduced component lists. This method may be efectively applied to calculating the minimum distance between two shapes which are generated by the CAD tool, like in the nesting system.

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Minimum Distance based Precoder Design for General MIMO Systems using Gram Matrix

  • Chen, Zhiyong;Xu, Xiaodong
    • Journal of Communications and Networks
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    • v.17 no.6
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    • pp.634-646
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    • 2015
  • Assuming perfect channel state information (CSI) at the transmitter and receiver, the optimization problem of maximizing the minimum Euclidean distance between two received signals by a linear precoder is considered for multiple-input multiple-output (MIMO) systems with arbitrary dimensions and arbitraryary quadrature amplitude modulation (QAM) input. A general precoding framework is first presented based on the Gram matrix, which is shown for 2-dimensional (2-D) and 3-dimensional (3-D) MIMO systems when employing the ellipse expanding method (EEM). An extended precoder for high-dimensional MIMO system is proposed following the precoding framework, where the Gram matrix for high-dimensional precoding matrix can be generated through those chosen from 2-D and 3-D results in association with a permutation matrix. A complexity-reduced maximum likelihood detector is also obtained according to the special structure of the proposed precoder. The analytical and numerical results indicate that the proposed precoder outperforms the other precoding schemes in terms of both minimum distance and bit error rate (BER).

Face Image Retrieval by Using Eigenface Projection Distance (고유영상 투영거리를 이용한 얼굴영상 검색)

  • Lim, Kil-Taek
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.5
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    • pp.43-51
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    • 2009
  • In this paper, we propose an efficient method of face retrieval by using PCA(principal component analysis) based features. The coarse-to-fine strategy is adopted to sort the retrieval results in the lower dimensional eigenface space and to rearrange candidates at high ranks in higher dimensional eigenface space. To evaluate similarity between a query face image and class reference image, we utilize the PD (projection distance), MQDF(modified quadratic distance function) and MED(minimum Euclidean distance). The experimental results show that the proposed method which rearrange the retrieval results incrementally by using projection distance is efficient for face image retrieval.

Weight Vector Analysis to Portfolio Performance with Diversification Constraints (비중 상한 제약조건에 따른 포트폴리오 성과에 대한 투자 비중 분석)

  • Park, Kyungchan;Kim, Hongseon;Kim, Seongmoon
    • Korean Management Science Review
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    • v.33 no.4
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    • pp.51-64
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    • 2016
  • The maximum weight of single stock in mutual fund is limited by regulations to enforce diversification. Under incomplete information with added constraints on portfolio weights, enhanced performance had been reported in previous researches. We analyze a weight vector to examine the effects of additional constraints on the portfolio's performance by computing the Euclidean distance from the in-sample tangency portfolio, as opposed to previous researches which analyzed ex-post return only. Empirical experiment was performed on Mean-variance and Minimum-variance model with Fama French's 30 industry portfolio and 10 industry portfolio for the last 1,000 months from August 1932 to November 2015. We find that diversification-constrained portfolios have 7% to 26% smaller Euclidean distances with the benchmark portfolio compared to those of unconstrained portfolios and 3% to 11% greater Sharpe Ratio.

The Image Compression Using the Central Vectors of Clusters (Cluster의 중심벡터를 이용하는 영상 압축)

  • Cho, Che-Hwang
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.1
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    • pp.5-12
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    • 1995
  • In the case where the set of training vectors constitute clusters, the codevectors of the codebook which is used to compression for speech and images in the vector quantization are regarded as the central vectors of the clusters constituted by given training vectors. In this work, we consider the distribution of Euclidean distance obtaining in the process of searching for the minimum distance between vectors, and propose the method searching for the proper number of and the central vectors of clusters. And then, the proposed method shows more than the about 4[dB] SNR than the LBG algorithm and the competitive learning algorithm

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Fixed Biased 4-D Multiple-Subcarrier Signal for Average Power Reduction in Optical Wireless Communication (Fixed bias를 가지는 4-D Multiple-Subcarrier 신호를 이용한 Optical Wireless 통신의 평균 전력 절감에 관한 연구)

  • 김해근
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.40 no.10
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    • pp.103-109
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    • 2003
  • We have proposed the 4-Dimensional Multiple-Subcarrier Modulation with fixed bias in Optical Wireless Communications. Here, the 4-D signal vectors are derived from the optimization technique of signal waveforms maximizing the minimum distance between signal points in an n-dimensional Euclidean sphere. The resulting vectors are used in generating the output amplitude of impulse generator in a Multiple-Subcarrier Modulation scheme. We have achieved that the normalized power requirement of the proposed system is maximum 3 dB and 3.3 dB smaller than those of normal QPSK, Reserved Subcarrier, and Minimum Power scheme, respectively. Also, in the range of 1.125 ∼ 1.25 of the normalized bandwidth, the proposed system has maximum 3 dB, 2 ∼ 4 dB, 0 ∼ 3 dB smaller bandwidth requirement compare to normal QPSK, Res. Subcarrier, Min. Power schemes, respectively.