• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.39 no.6
• /
• pp.268-276
• /
• 2002

This paper introduces the high-resolution channel estimation technique which are used to estimate the first arrival multipath delay component. The proposed technique yields the precise estimate of the first time arrival which is directly related to the performance of TDOA-based position location. The proposed technique utilizes the transformed auto-correlation function of received common pilot signal in frequency domain, its samples compose the hermitian Toeplitz matrix at sequel. Then the time delay components could be estimated with precision by the analysis of eigen-structure of corresponding matrix. In this paper, obeying the modified CODIT model, the performance of the PR-IPDL(Pseudo Random-Idle Period Downlink) and TA-IPDL(Time Aligned-Idle Period Downlink considered as 3GPP position location technique will be exploited systematically through the computer simulations with applying the proposed technique.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.12 no.4_1
• /
• pp.67-76
• /
• 1992

A hierarchical formulation based on p-version of the finite element method for linear elastic axisymmetric stress analysis is presented. This is accomplished by introducing additional nodal variables in the element displacement approximation on the basis of integrals of Legendre polynomials. Since the displacement approximation is hierarchical, the resulting element stiffness matrix and equivalent nodal load vectors are hierarchical also. The merits of the propoosed element are as follow: i) improved conditioning, ii) ease of joining finite elements of different polynomial order, and iii) utilizing previous solutions and computation when attempting a refinement. Numerical examples are presented to demonstrate the accuracy, efficiency, modeling convenience, robustness and overall superiority of the present formulation. The results obtained from the present formulation are also compared with those available in the literature as well as with the analytical solutions.

• Journal of Korea Multimedia Society
• /
• v.16 no.4
• /
• pp.453-463
• /
• 2013

In this paper, we present an effective method and a system for the music summarization which automatically extract the chorus portion of a piece of music. A music summary technology is very useful for browsing a song or generating a sample music for an online music service. To develop the solution, conventional automatic music summarization methods use a 2-dimensional similarity matrix, statistical models, or clustering techniques. But our proposed method extracts the music summary by calculating BER(Bit Error Rate) between audio fingerprint blocks which are extracted from a song. But we could directly use an enormous audio fingerprint database which was already saved for a music retrieval solution. This shows the possibility of developing a various of new algorithms and solutions using the audio fingerprint database. In addition, experiments show that the proposed method captures the chorus of a song more effectively than a conventional method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.3
• /
• pp.297-303
• /
• 2009

In this paper, we propose the biomedical spectral pattern classification techniques by the fusion scheme based on the SpPCA and MLP in extended feature space. A conventional PCA technique for the dimension reduction has the problem that it can't find an optimal transformation matrix if the property of input data is nonlinear. To overcome this drawback, we extract features by the SpPCA technique in extended space which use the local patterns rather than whole patterns. In the classification step, individual classifier based on MLP calculates the similarity of each class for local features. Finally, biomedical spectral patterns is classified by the fusion scheme to effectively combine the individual information. As the simulation results to verify the effectiveness, the proposed method showed more improved classification results than conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.3C
• /
• pp.419-425
• /
• 2004

This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera. Our approach is to only compute three vanishing points without informations such as the focal length and rotation matrix from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector v. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.6_1
• /
• pp.575-581
• /
• 2012

In general, various modeling and estimation techniques have been proposed to extract the tropospheric and ionospheric delays from the GPS CORS. In this study, Kalman filter approach is adopted to estimate the tropospheric and ionospheric delays and the proper modeling for the state vector and the variance-covariance matrix for the process noises are performed. The coordinates of reference stations and the zenith wet delays are estimated with the assumption of random walk stochastic process. Also, the first-order Gauss-Markov stochastic process is applied to compute the ionospheric effects. For the evaluation of the proposed modeling technique, Kalman filter algorithm is implemented and the numerical test is performed with the CORS data. The results show that the atmospheric effects can be estimated successfully and, as a consequence, can be used for the generation of VRS data.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.2
• /
• pp.149-157
• /
• 2011

Undecided inference could be regarded as a missing data problem such as MARand MNAR. Under the assumption of MAR, undecided inference make use of logistic regression model. The probability of default for the undecided group is obtained with regression coefficient vectors for the decided group and compare with the probability of default for the decided group. And under the assumption of MNAR, undecide dinference make use of logistic regression model with additional feature random vector. Simulation results based on two kinds of real data are obtained and compared. It is found that the misclassification rates are not much different from the rate of rawdata under the assumption of MAR. However the misclassification rates under the assumption of MNAR are less than those under the assumption of MAR, and as the ratio of the undecided group is increasing, the misclassification rates is decreasing.

• The Journal of the Acoustical Society of Korea
• /
• v.24 no.4
• /
• pp.210-216
• /
• 2005

We Propose a new feature normalization scheme based on eigenspace for achieving robust speech recognition. In general, mean and variance normalization (MVN) is Performed in cepstral domain. However, another MVN approach using eigenspace was recently introduced. in that the eigenspace normalization Procedure Performs normalization in a single eigenspace. This Procedure consists of linear PCA matrix feature transformation followed by mean and variance normalization of the transformed cepstral feature. In this method. 39 dimensional feature distribution is represented using only a single eigenspace. However it is observed to be insufficient to represent all data distribution using only a sin91e eigenvector. For more specific representation. we apply unique na independent eigenspaces to cepstra, delta and delta-delta cepstra respectively in this Paper. We also normalize training data in eigenspace and get the model from the normalized training data. Finally. a feature space rotation procedure is introduced to reduce the mismatch of training and test data distribution in noisy condition. As a result, we obtained a substantial recognition improvement over the basic eigenspace normalization.

• The Korean Journal of Applied Statistics
• /
• v.30 no.4
• /
• pp.579-590
• /
• 2017

The multivariate empirical distribution function could be defined when its distribution function can be estimated. It is known that bivariate empirical distribution functions could be visualized by using Step plot and Quantile plot. In this paper, the multivariate empirical distribution plot is proposed to represent the multivariate empirical distribution function on the unit square. Based on many kinds of empirical distribution plots corresponding to various multivariate normal distributions and other specific distributions, it is found that the empirical distribution plot also depends sensitively on its distribution function and correlation coefficients. Hence, we could suggest five goodness-of-fit test statistics. These critical values are obtained by Monte Carlo simulation. We explore that these critical values are not much different from those in text books. Therefore, we may conclude that the proposed test statistics in this work would be used with known critical values with ease.

• Journal of KIISE:Information Networking
• /
• v.30 no.2
• /
• pp.143-154
• /
• 2003

There is a growing trend in developing system for distributed mobile system that supports services - job flow management, video conference, replicated data management and resource allocation. Supporting these services, applications have to use causally ordered message delivery. Previous proposals that provide causally ordered message delivery have problems such as communication overhead, message delaying, scalability, computing overload of mobile host. In this paper, we proposed efficient protocol for causally ordered message delivery using the methods that MSS maintains dependency information matrix between MSS and MH, Piggybacking dependency information about each immediate predecessor message. Proposed algorithm, when compared with previous proposals, provides a low message overhead, and low probability of unnecessary inhibition in delivering messages. Also, it consider resource restriction of MH and low bandwidth of wireless communication by computing most of algorithm at MSS, and reduce processing delay by executing causally ordered message delivery a unit of MH.