• 제목/요약/키워드: metric distance

검색결과 257건 처리시간 0.024초

Channel Coding-Aided Multi-Hop Transmission for Throughput Enhancement

  • Hwang, Inchul;Wang, Hanho
    • International Journal of Contents
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    • 제12권1호
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    • pp.65-69
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    • 2016
  • Wireless communication chipsets have fixed transmission rate and communication distance. Although there are many kinds of chipsets with throughput and distance purpose, they cannot support various types of wireless applications. This paper provides theoretic research results in order to support various wireless applications requiring different throughput, delayed quality-of-service (QoS), and different communication distances by using a wireless communication chipset with fixed rate and transmission power. As a performance metric, the probability for a data frame that successfully receives at a desired receiver is adopted. Based on this probability, the average number of transmission in order to make a successful frame transmission is derived. Equations are utilized to analyze the performance of a single-hop with channel coding and a dual-hop without error correction matter transmission system. Our results revealed that single-hop transmission assisted by channel coding could extend its communication distance. However, communication range extending effect of the single-hop system was limited. Accordingly, dual-hop transmission is needed to overcome the communication distance limit of a chipset.

An Efficient Video Retrieval Algorithm Using Key Frame Matching for Video Content Management

  • Kim, Sang Hyun
    • International Journal of Contents
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    • 제12권1호
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    • pp.1-5
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    • 2016
  • To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

An Efficient Video Retrieval Algorithm Using Color and Edge Features

  • Kim Sang-Hyun
    • 융합신호처리학회논문지
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    • 제7권1호
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    • pp.11-16
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    • 2006
  • To manipulate large video databases, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-w]so user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm to extract key frames using color histograms and to match the video sequences using edge features. To effectively match video sequences with low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with several real sequences show that the proposed video retrieval algorithm using color and edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

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A Study on the Optimal Mahalanobis Distance for Speech Recognition

  • Lee, Chang-Young
    • 음성과학
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    • 제13권4호
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    • pp.177-186
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    • 2006
  • In an effort to enhance the quality of feature vector classification and thereby reduce the recognition error rate of the speaker-independent speech recognition, we employ the Mahalanobis distance in the calculation of the similarity measure between feature vectors. It is assumed that the metric matrix of the Mahalanobis distance be diagonal for the sake of cost reduction in memory and time of calculation. We propose that the diagonal elements be given in terms of the variations of the feature vector components. Geometrically, this prescription tends to redistribute the set of data in the shape of a hypersphere in the feature vector space. The idea is applied to the speech recognition by hidden Markov model with fuzzy vector quantization. The result shows that the recognition is improved by an appropriate choice of the relevant adjustable parameter. The Viterbi score difference of the two winners in the recognition test shows that the general behavior is in accord with that of the recognition error rate.

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The Implementation of RRTs for a Remote-Controlled Mobile Robot

  • Roh, Chi-Won;Lee, Woo-Sub;Kang, Sung-Chul;Lee, Kwang-Won
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.2237-2242
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    • 2005
  • The original RRT is iteratively expanded by applying control inputs that drive the system slightly toward randomly-selected states, as opposed to requiring point-to-point convergence, as in the probabilistic roadmap approach. It is generally known that the performance of RRTs can be improved depending on the selection of the metrics in choosing the nearest vertex and bias techniques in choosing random states. We designed a path planning algorithm based on the RRT method for a remote-controlled mobile robot. First, we considered a bias technique that is goal-biased Gaussian random distribution along the command directions. Secondly, we selected the metric based on a weighted Euclidean distance of random states and a weighted distance from the goal region. It can save the effort to explore the unnecessary regions and help the mobile robot to find a feasible trajectory as fast as possible. Finally, the constraints of the actuator should be considered to apply the algorithm to physical mobile robots, so we select control inputs distributed with commanded inputs and constrained by the maximum rate of input change instead of random inputs. Simulation results demonstrate that the proposed algorithm is significantly more efficient for planning than a basic RRT planner. It reduces the computational time needed to find a feasible trajectory and can be practically implemented in a remote-controlled mobile robot.

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시공간 블록부호(STBC)가 결합된 TCM 디코더 설계에 관한 연구 (A Study on Design of a Low Complexity TCM Decoder Combined with Space-Time Block Codes)

  • 박철현;정윤호;이서구;김근회;김재석
    • 한국통신학회논문지
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    • 제29권3A호
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    • pp.324-330
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    • 2004
  • 본 논문에서는 STBC (space tine block codes)의 채널 정보를 이용하여 TCM(Trellis Coded Modulation) 복호기의 연산량을 감소시키는 복호 방법을 제안하였고 이를 하드웨어로 설계 및 검증한 결과를 제시한다. 제안한 방법은 바이어스 포인트 설정을 이용하여 부집합에 n개의 시그널 포인트가 존재할 경우 실제 TCM 복호기에서 연산되는 가지 값을 부집합에서 1개의 시그널 포인트만 필요로 한다. 그러므로 바이어스 포인트 설정을 사용하여 가장 가까운 시그널 포인트를 미리 찾아내어 연산량을 l/n로 줄일 수 있다. 16QAM 8subset 경우에 AED (absolute euclidean distance)연산을 하게 되면 곱셈은 37%, 가감산 41%, 비교는 25%의 연산량 감소 효과가 있다. 또한 본 논문에서는 제안된 STBC와 TCM이 결합된 복호기의 하드웨어 합성 결과를 제시한다. 논리 합성 결과 약 87.6K개의 게이트가 요구됨을 확인하였다.

The extension of the largest generalized-eigenvalue based distance metric Dij1) in arbitrary feature spaces to classify composite data points

  • Daoud, Mosaab
    • Genomics & Informatics
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    • 제17권4호
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    • pp.39.1-39.20
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    • 2019
  • Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate analysis. In this paper, data points are heterogeneous sets of biosequences (composite data points). A composite data point is a set of ordinary data points (e.g., set of feature vectors). We theoretically extend the derivation of the largest generalized eigenvalue-based distance metric Dij1) in any linear and non-linear feature spaces. We prove that Dij1) is a metric under any linear and non-linear feature transformation function. We show the sufficiency and efficiency of using the decision rule $\bar{{\delta}}_{{\Xi}i}$(i.e., mean of Dij1)) in classification of heterogeneous sets of biosequences compared with the decision rules min𝚵iand median𝚵i. We analyze the impact of linear and non-linear transformation functions on classifying/clustering collections of heterogeneous sets of biosequences. The impact of the length of a sequence in a heterogeneous sequence-set generated by simulation on the classification and clustering results in linear and non-linear feature spaces is empirically shown in this paper. We propose a new concept: the limiting dispersion map of the existing clusters in heterogeneous sets of biosequences embedded in linear and nonlinear feature spaces, which is based on the limiting distribution of nucleotide compositions estimated from real data sets. Finally, the empirical conclusions and the scientific evidences are deduced from the experiments to support the theoretical side stated in this paper.

MIMO System을 위한 Path Metric 비교 기반 적응형 K-best 알고리즘 (An Adaptive K-best Algorithm Based on Path Metric Comparison for MIMO Systems)

  • 김봉석;최권휴
    • 한국통신학회논문지
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    • 제32권11A호
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    • pp.1197-1205
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    • 2007
  • Adaptive K-best 검출 방식은 MIMO system을 위해 제안된 알고리즘이다. 제안된 방식은 각 K-best 단계에서 Zero-Forcing(ZF) 추정치의 신뢰도의 정도를 기반으로 하여, 생존 path들의 개수인 K값을 바꾸는 방식이다. 고정된 K값을 사용하는 K-best 방식의 치명적인 단점은 잘못된 ZF 추정치에 의해 발생하는 불완전한 간섭 제거로 인해 올바른 path임에도 일시적으로 그 거리가 K개의 최소 path 거리들 보다 더 커질 수 있다. 잘못된 ZF 추정치가 발생된 경우에는, path들 간의 거리들이 뚜렷하게 다르지 않다는 것을 관찰을 통해 발견하였다. 본 논문에서는 ZF 추정치의 신뢰도를 나타내는 지표로, 최소값을 갖는 path의 거리와 두 번째 최소값을 가지는 path 거리의 비를 사용한다. 최소값을 가지는 두 path의 거리의 비를 근거로, K값을 적절하게 선택하는 제안된 방식은 기존의 고정된 K값을 사용하는 K-best 방식에 비해, 확연히 개선되었음을 보여준다. 제안된 방식은, 큰 K값을 사용하는 방식에 비해 평균 계산양은 매우 작으면서, 큰 K값을 사용한 방식의 성능을 가진다.

연관성 기반 비유사성을 활용한 범주형 자료 군집분석 (Categorical Data Clustering Analysis Using Association-based Dissimilarity)

  • 이창기;정욱
    • 품질경영학회지
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    • 제47권2호
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    • pp.271-281
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    • 2019
  • Purpose: The purpose of this study is to suggest a more efficient distance measure taking into account the relationship between categorical variables for categorical data cluster analysis. Methods: In this study, the association-based dissimilarity was employed to calculate the distance between two categorical data observations and the distance obtained from the association-based dissimilarity was applied to the PAM cluster algorithms to verify its effectiveness. The strength of association between two different categorical variables can be calculated using a mixture of dissimilarities between the conditional probability distributions of other categorical variables, given these two categorical values. In particular, this method is suitable for datasets whose categorical variables are highly correlated. Results: The simulation results using several real life data showed that the proposed distance which considered relationships among the categorical variables generally yielded better clustering performance than the Hamming distance. In addition, as the number of correlated variables was increasing, the difference in the performance of the two clustering methods based on different distance measures became statistically more significant. Conclusion: This study revealed that the adoption of the relationship between categorical variables using our proposed method positively affected the results of cluster analysis.

슬라이딩(Sliding) 다중 심벌 간파를 이용한 드렐리스 부호화된 MDPSK (Trellis-coded MDPSK with Sliding Multiple Symbol Detection)

  • 박이홍;전찬우;박성경;김종일;강창언
    • 전자공학회논문지A
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    • 제31A권6호
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    • pp.1-8
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    • 1994
  • In this paper, in order to apply the idea MDPSK to TCM, we use signal set expansion and set partition by phase differences. Through this we propose the trellis-coded MDPSK. And the Viterbi decoder containing branch metrics of the squared Euclidean distance of the Lth order phase difference as well as the first order phase difference is introduced in order to improve the bit error rate(BER) in the differential detection of the trellis-coded MDPSK. The proposed Viterbi decoder is conceptually same to the sliding multiple symbol dection method which uses the branch metric with the first and Lth order phase differences. We investigate the performance of the uncoded DQPSK and the trallis-coded D8PSK in additive white Gaussian noise (AWGN) through the Monte Carlo simulation under the two cases of using and not using the Lth order phase difference metric. The study shows that trellis-coded 8DPSK is an attractive scheme for power and bandlimited systems while also improving the BER performance when the Viterbi decoder is employed to the Lth order phase order difference metric. This performance improvement has been obtained without sacrificing the bandwidth or the power efficiency.

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