• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.75-81
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• 2017

This paper estimate a desired signal in a correlation wireless communication. The transmitted signal is mixed with the information signal, interference, and noise in wireless channel, and it is incident on the receiver. In this paper, we apply MUSIC algorithm and sub-array method to recover the total rank of the correlation matrix in order to estimation a desired signal among receiving signals. Through simulation, we analyze to compare the proposed method with the classical MUSIC algorithm. As a result of the simulation, the proposed method improved the resolution about 10degrees compared to the conventional MUSIC algorithm. We prove the superiority of the proposed method for the desired signal estimation in correlation channel.

• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.1-12
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• 2004

This paper estimated the arrival angle and electric wave delay time using the space method law and the directions of arrival (DOA) estimation algorithm in case of signal correlation. Space method law is the method used to repress cross correlation before applying the weight value to the receiving signal. The values of the diagonal elements in the correlation matrix were averaged to replace as the diagonal elements value. In the area of wireless communication or mobile communication, there are high correlations in case of low delay time difference in multiple waves. This causes the quality of the communication to drop due to interference with the desired signal elements. This paper estimated the arrival angle and electric wave delay time using the space method law and the MUSIC algorithm. With the arrival angle algorithm, the arrival angle cannot be estimated below 5 in case of signal correlations because the angle resolution capacity decreases accordingly. The super resolution capacity was estimated to determine the arrival angle below 5 in this paper. In addition, the proposed algorithm estimated the short delay time difference to be below 20ns.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.5
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• pp.430-437
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• 2016

In general, noise measurement results show larger random ripple than those of the network analyzer. The reason for the lager random ripple of the noise measurements is considered that the general noise measurements uses absolute measured noise powers, while the network analyzer measures using a ratio of the measured powers. In this paper, a novel measurement method of noise correlation matrix using relative noise ratios is proposed. Proposed method measures the five noise powers of DUT for the five input impedance variations and the four relative noise ratios are formed using the five measured noise powers. The four noise ratios are used to compute the noise correlation matrix and noise parameters. The resulting noise parameters for a 0.5 dB attenuator show good agreements with theoretical values calculated by S-parameters. Also, the noise parameters of an active DUT with a noise figure of less than 1 dB are measured and the measured results show a small random ripple as expected and their values are physically acceptable. In conclusion, the proposed method can be applied to the noise parameter measurements for DUT with a noise figure below 1 dB.

• 전자공학회논문지 IE
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• v.48 no.1
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• pp.7-15
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• 2011

In this paper, we propose a correlation-based subspace estimation technique, which is called square-root forward/backward correlation-based projection approximation subspace tracking(SRFB-COPAST). The SRFB-COPAST utilizes the forward and backward correlation matrix as well as square-root recursive matrix update in projection approximation approach to develop the subspace tracking algorithm. With the projection approximation, the square-root recursive FB-COPAST is presented. The proposed algorithm has the better performance than the recently developed COPAST method.

• ETRI Journal
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• v.40 no.2
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• pp.197-206
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• 2018

Multiple-input multiple-output (MIMO) systems offer significant enhancements in terms of their data rate and channel capacity compared to traditional systems. However, correlation degrades the system performance and imposes practical limits on the number of antennas that can be incorporated into portable wireless devices. The use of switched parasitic antennas (SPAs) is a possible solution, especially where it is difficult to obtain sufficient signal decorrelation by conventional means. The covariance matrix represents the correlation present in the propagation channel, and has significant impact on the MIMO channel capacity. The results of this work demonstrate a significant improvement in the MIMO channel capacity by using SPA with the knowledge of the covariance matrix for all pattern configurations. By employing the "water-pouring algorithm" to modify the covariance matrix, the channel capacity is significantly improved compared to traditional systems, which spread transmit power uniformly across all the antennas. A condition number is also proposed as a selection metric to select the optimal pattern configuration for MIMO-SPAs.

• The Journal of the Korean dental association
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• v.54 no.11
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• pp.850-864
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• 2016

The Generalized Estimating Equations (GEE) approach is a widely used statistical method for analyzing longitudinal data and clustered data in clinical studies. In dentistry, due to multiple outcomes obtained from one patient, the outcomes produced from an individual patient are correlated with one another. This study focused on the basic ideas of GEE and introduced the types of covariance matrix and working correlation matrix. The quasi-likelihood information criterion (QIC) and quasi-likelihood information criterion approximation ($QIC_u$) were used to select the best working correlation matrix and the best fitting model for the correlated outcomes. The purpose of this study is to show a detailed process for the GEE analysis using SPSS software along with an orthodontic miniscrew example, and to help understand how to use GEE analysis in dental research.

• Journal of the Korea Safety Management & Science
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• v.2 no.4
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• pp.113-124
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• 2000

First, in order to improve selecting method of quality characteristic level desired by customers, S/N(Signal-to-Noise) ratio of Taguchi in larger-the-better characteristics was applied. Second, the Matrix classification standard of ACE(Attribute Categorization Evaluation) is presented using KANO model on difference analysis of importance and satisfaction through questionnaire from customers. This is for reflecting the diverse EC which customers want in EC quality sufficiently. Also, establishing sales point will be helpful in business strategy through presenting types that are able to decide planning quality. Third, the important measure of EC about correlation among quality characteristics and a new weight of EC are calculated depending on importance of EC and the weight of customer attribute and materials of relationship matrix through correlation matrix analysis.

• Proceedings of the Safety Management and Science Conference
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• 2000.05a
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• pp.481-490
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• 2000

First, in order to improve selecting method of quality characteristic level desired by customers, S/H(Signal-to-Noise) ratio of Taguchi in larger-the-better characteristics was applied. Second, the Matrix classification standard of ACE(Attribute Categorization Evaluation) is presented using KANO model on difference analysis of importance and satisfaction through questionnaire from customers. This is for reflecting the diverse EC which customers want in EC quality sufficiently. Also, establishing sales point will be helpful in business strategy through presenting types that are able to decide planning quality. Third, the important measure of EC about correlation among quality characteristics and a new weight o( EC are calculated depending on importance of EC and the weight of customer attribute and materials of relationship matrix through correlation matrix analysis.

• ETRI Journal
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• v.36 no.4
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• pp.545-553
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• 2014

This paper proposes an algorithm to sense orthogonal frequency-division multiplexing (OFDM) signals in cognitive radio (CR) systems. The basic idea behind this study is when a primary user is occupying a wireless channel, the covariance matrix is non-diagonal because of the time domain cross-correlation of the cyclic prefix (CP). In light of this property, a new decision metric that measures the power of the data found on two minor diagonals in the covariance matrix related to the CP is introduced. The impact of synchronization errors on the signal detection is analyzed. Besides this, a likelihood-ratio test is proposed according to the Neyman-Pearson criterion after deriving probability distribution functions of the decision metric under hypotheses of signal presence and absence. A threshold, subject to the requirement of probability of false alarm, is derived; also the probabilities of detection and false alarm are computed accordingly. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed algorithm.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.927-936
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• 2017

To analyze longitudinal count data, Poisson linear mixed models are commonly used. In the models the random effects covariance matrix explains both within-subject variation and serial correlation of repeated count outcomes. When the random effects covariance matrix is assumed to be misspecified, the estimates of covariates effects can be biased. Therefore, we propose reasonable and flexible structures of the covariance matrix using autoregressive and moving average Cholesky decomposition (ARMACD). The ARMACD factors the covariance matrix into generalized autoregressive parameters (GARPs), generalized moving average parameters (GMAPs) and innovation variances (IVs). Positive IVs guarantee the positive-definiteness of the covariance matrix. In this paper, we use the ARMACD to model the random effects covariance matrix in Poisson loglinear mixed models. We analyze epileptic seizure data using our proposed model.