• Title/Summary/Keyword: Probability Vector

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GPU-based Stereo Matching Algorithm with the Strategy of Population-based Incremental Learning

  • Nie, Dong-Hu;Han, Kyu-Phil;Lee, Heng-Suk
    • Journal of Information Processing Systems
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    • v.5 no.2
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    • pp.105-116
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    • 2009
  • To solve the general problems surrounding the application of genetic algorithms in stereo matching, two measures are proposed. Firstly, the strategy of simplified population-based incremental learning (PBIL) is adopted to reduce the problems with memory consumption and search inefficiency, and a scheme for controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities. In addition, an alternative version of the proposed algorithm, without the use of a probability vector, is also presented for simpler set-ups. Secondly, programmable graphics-hardware (GPU) consists of multiple multi-processors and has a powerful parallelism which can perform operations in parallel at low cost. Therefore, in order to decrease the running time further, a model of the proposed algorithm, which can be run on programmable graphics-hardware (GPU), is presented for the first time. The algorithms are implemented on the CPU as well as on the GPU and are evaluated by experiments. The experimental results show that the proposed algorithm offers better performance than traditional BMA methods with a deliberate relaxation and its modified version in terms of both running speed and stability. The comparison of computation times for the algorithm both on the GPU and the CPU shows that the former has more speed-up than the latter, the bigger the image size is.

A Study on the Performance Analysis of Asynchronous Repeated FH/MFSK System (비동기 FH/MFSK 반복전송 시스템의 성능분석)

  • 지영호;한영렬
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.13 no.2
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    • pp.120-126
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    • 1988
  • In this paper the performance of the asynchronous Repeated FH/MFSK system for the CDMA(Code Division Multiple Access) was analyzed. Actually there was no difference in the probabilities of hit of frequency between Random Coding method and frequency hopping pattern vector suggested by Einarsso. Actual situation was adopted as a model in thie simulation, on the assumption thet;a:there was no Noise, Multipath propagation, b:there was only mutual interference. c:the number of users M was given. Also it was found that there is almost no deviation between the value calculated from the formula of word error probability expressed by bound and that obtained from this simulation.

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Performance Improvement of 2-Frame PTV Method Using an Adaptive Hybrid Scheme (적응형 하이브리드 기법을 이용한 2-Frame PTV 기법의 성능향상 연구)

  • Kim, Hyoung-Bum;Lee, Sang-Joon
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.24 no.3
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    • pp.443-449
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    • 2000
  • The performance of 2-frame PTV(particle tracking velocimetry) system was improved using an adaptive hybrid scheme. The original 2-frame PTV method based on the match probability concept employs global match parameters for the entire flow field. Since this does not reflect fully the detailed local velocity change, it sometimes reduces the recovery rate of velocity vectors and increases the number of erroneous vectors in the region where an extraordinary flow structure exists. In this study, the preliminary FFT-based PIV results are used as an input parameter to determine the local match parameters needed for the 2-frame particle tracking algorithm. A computer simulation using synthetic particle images was carried out to study the performance of the adaptive 2-frame PTV technique. The adaptive hybrid method shows the better performance with increasing the velocity vector recovery rate and decreasing the computation time, compared to the original 2-frame PTV method.

Decomposition of category mixture in a pixel and its application for supervised image classification

  • Matsumoto, Masao;Arai, Kohei;Ishimatsu, Takakazu
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.514-519
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    • 1992
  • To make an accurate retrieval of the proportion of each category among mixed pixels (Mixel's) of a remotely sensed imagery, a maximum likelihood estimation method of category proportion is proposed. In this method, the observed multispectral vector is considered as probability variables along with the approximation that the supervised data of each category can be characterized by normal distribution. The results show that this method can retrieve accurate proportion of each category among Mixel's. And a index that can estimate the degree of error in each category is proposed. AS one of the application of the proportion estimation, a method for image classification based on category proportion estimation is proposed. In this method all pixel in a remotely sensed imagery are assumed to be Mixel's, and are classified to most dominant category. Among the Mixel's, there exists unconfidential pixels which should be categorized as unclassified pixels. In order to discriminate them, two types of criteria, Chi square and AIC, are proposed for fitness test on pure pixel hypothesis. Experimental result with a simulated dataset show an usefulness of proposed classification criterion compared to the conventional maximum likelihood criterion and applicability of the fitness tests based on Chi square and AIC,

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The Convergence Characteristics of The Time-Averaged Distortion in Vector Quantization: Part II. Applications to Testing Trained Codebooks (벡터 앙자화에서 시간 평균 왜곡치의 수렴 특성: II. 훈련된 부호책의 감사 기법)

  • Dong Sik Kim
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.5
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    • pp.747-755
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    • 1995
  • When codebooks designed by a clustering algorithm using training sets, a time-averaged distortion, which is called the inside-training-set- distortion (ITSD), is usually calculated in each iteration of the algorithm, since the input probability function is unknown in general. The algorithm stops if the ITSD no more significantly decreases. Then, in order to test the trained codebook, the outside-training-set-distortion (OTSD) is to be calculated by a time-averaged approximation using the test set. Hence codebooks that yield small values of the OTSD are regarded as good codebooks. In other words, the calculation of the OTSD is a criterion to testing a trained codebook. But, such an argument is not always true if some conditions are not satisfied. Moreover, in order to obtain an approximation of the OTSD using the test set, it is known that a large test set is requared in general. But, large test set causes heavy calculation com0plexity. In this paper, from the analyses in [16], it has been revealed that the enough size of the test set is only the same as that of the codebook when codebook size is large. Then a simple method to testing trained codebooks is addressed. Experimental results on synthetic data and real images supporting the analysis are also provided and discussed.

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Half-pixel Accuracy Motion Estimation Using the Correlation of Motion Vectors (움직임벡터의 상관성을 이용한 반화소단위 움직임 추정 기법)

  • Lee, Bub-Ki;Lee, Kyeong-Hwan;Choi, Jung-Hyun;Kim, Duk-Gyoo
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.6
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    • pp.119-126
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    • 1998
  • In this paper, we proposed two new methods of half-pel accuracy motion estimation using spatial correlation of half-pel accuracy motion vectors and stochastic characteristics between pixel accuracy motion vectors and half-pel accuracy motion vectors. We confirmed two facts : One is that the probability of having same half-pel accuracy motion vectors with neighboring blocks is high when having same pixel accuracy motion vectors. And the other is that there is high correlation between neighboring half-pel positions. These new half-pel motion estimation technique are shown to decrease the bit rates for vector coding and computational complexity with similar PSNR.

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Quasiclassical Trajectory Calculations for the Reaction Ne + H2+ → NeH+ + H

  • Wang, Yuliang;Tian, Baoguo;Qu, Liangsheng;Chen, Juna;Li, Hui
    • Bulletin of the Korean Chemical Society
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    • v.32 no.12
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    • pp.4210-4214
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    • 2011
  • Quasiclassical trajectory (QCT) calculations of Ne + ${H_2}^+$ reaction have been carried out on the adiabatic potential energy surface of the ground state $1^2$ A'. The reaction probability of the title reaction for J = 0 has been calculated, and the QCT result is consistent with the previous quantum mechanical wave packet result. Quasiclassical trajectory calculations of the four polarization-dependent differential cross sections have been carried out in the center of mass (CM) frame. The P(${\theta}_r$), P(${\phi}_r$) and P(${\theta}_r$, ${\phi}_r$) distributions, the k-k'-j' correlation and the angular distribution of product rotational vectors are presented in the form of polar plots. Due to the well in $1^2$ A' PES, the reagent vibrational excitation has greater influence on the polarization of the product rotational angular momentum vectors j' than the collision energy.

Adaptive Feedback Interference Cancellation Algorithm Using Correlations for Adaptive Interference Cancellation System (적응 간섭 제거 시스템을 위한 상관도를 적용한 적응적 궤환 간섭 제거 알고리즘)

  • Han, Yong-Sik;Yang, Woon-Geun
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.21 no.4
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    • pp.427-432
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    • 2010
  • To reduce the outage probability and to increase the transmission capacity, the importance of repeaters in cellular systems is increasing. But a RF(Radio Frequency) repeater has a problem that the output of the transmit antenna is partially feedback to the receive antenna, which is feedback interference. In this paper, we proposed adaptive Sign-Sign LMS(Least Mean Square) algorithm using correlations for the performance enhancement of RF repeater. The weight vector is updated by using sign of input signal and error signal to the least squared error of the conventional algorithms. When compared with the conventional method, the proposed canceller achieves the maximum 10 dB performance gain in terms of the MSE(Mean Square Error).

QUALITY IMPROVEMENT OF COMPRESSED COLOR IMAGES USING A PROBABILISTIC APPROACH

  • Takao, Nobuteru;Haraguchi, Shun;Noda, Hideki;Niimi, Michiharu
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.520-524
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    • 2009
  • In compressed color images, colors are usually represented by luminance and chrominance (YCbCr) components. Considering characteristics of human vision system, chrominance (CbCr) components are generally represented more coarsely than luminance component. Aiming at possible recovery of chrominance components, we propose a model-based chrominance estimation algorithm where color images are modeled by a Markov random field (MRF). A simple MRF model is here used whose local conditional probability density function (pdf) for a color vector of a pixel is a Gaussian pdf depending on color vectors of its neighboring pixels. Chrominance components of a pixel are estimated by maximizing the conditional pdf given its luminance component and its neighboring color vectors. Experimental results show that the proposed chrominance estimation algorithm is effective for quality improvement of compressed color images such as JPEG and JPEG2000.

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The Unified Framework for AUC Maximizer

  • Jun, Jong-Jun;Kim, Yong-Dai;Han, Sang-Tae;Kang, Hyun-Cheol;Choi, Ho-Sik
    • Communications for Statistical Applications and Methods
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    • v.16 no.6
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    • pp.1005-1012
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    • 2009
  • The area under the curve(AUC) is commonly used as a measure of the receiver operating characteristic(ROC) curve which displays the performance of a set of binary classifiers for all feasible ratios of the costs associated with true positive rate(TPR) and false positive rate(FPR). In the bipartite ranking problem where one has to compare two different observations and decide which one is "better", the AUC measures the quantity that ranking score of a randomly chosen sample in one class is larger than that of a randomly chosen sample in the other class and hence, the function which maximizes an AUC of bipartite ranking problem is different to the function which maximizes (minimizes) accuracy (misclassification error rate) of binary classification problem. In this paper, we develop a way to construct the unified framework for AUC maximizer including support vector machines based on maximizing large margin and logistic regression based on estimating posterior probability. Moreover, we develop an efficient algorithm for the proposed unified framework. Numerical results show that the propose unified framework can treat various methodologies successfully.