• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.137-142
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• 2013

Direction of arrival is estimating for desire signal direction among received signal on antenna in spatial. In this paper, we were an estimation a receiving signal direction of arrival using multi beam forming in radar. We proposed, by signal direction of arrival estimation method, an algorithm which combine spatial correlation matrix weight value and beam steering algorithm in this paper. Through simulation, we were analysis a performance to compare general algorithm and proposal algorithm. In direction of arrival estimation, proposed algorithm is effectivity to decrease processing time because it is not doing an eigen decomposition. We showed that proposal algorithm improve more target estimation than general algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1551-1557
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• 2013

A current velocity measurement radar estimates Doppler frequencies to extract the corresponding surface velocity information. Therefore, it is required to maintain the high degree of reliability and accuracy of Doppler frequency estimates. However, Doppler spectra of water surface return echoes can have very widely varying shapes according to measurement environments and weather conditions. Therefore, serious problems may arise in maintaining the reliability and accuracy of conventional velocity estimating algorithm in a radar sensor. Therefore, in this paper, a newly suggested algorithm is proposed for improvement using estimation of peak Doppler frequencies. The proposed method shows that the more accurate velocity measurement can be possible comparing with the conventional one.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.84-93
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• 2010

This paper describes a method of visualization and fast estimation of parameter in continuous time signal. The parameter estimation method of this paper directly estimate the parameters on the basis of the discrete Fourier transform. Also, this paper present to efficient visualization method of dominant parameters obtained in continuous time signal. The proposed methods are applied to test functions with three dominant modes. The results show that the proposed methods are highly applicable to parameter estimation and visualization in continuous time signal.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.352-361
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• 2013

Combining multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) with a massive number of transmit antennas (massive MIMO-OFDM) is an attractive way of increasing the spectrum efficiency or reducing the transmission energy per bit. The effectiveness of Massive MIMO-OFDM is strongly affected by the channel state information (CSI) estimation method used. The overheads of training frame transmission and CSI feedback decrease multiple access channel (MAC) efficiency and increase the CSI estimation cost at a user station (STA). This paper proposes a CSI estimation scheme that reduces the training frame length by using a novel pilot design and a novel unitary matrix feedback method. The proposed pilot design and unitary matrix feedback enable the access point (AP) to estimate the CSI of the signal space of all transmit antennas using a small number of training frames. Simulations in an IEEE 802.11n channel verify the attractive transmission performance of the proposed methods.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1271-1275
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• 1987

With the stochastic process which consists of the harmonic sinusoid and the white nosie, the power spectrum of background EEG is estimated by the Pisarenko Harmonic Decomposition. The estimating results are examined and compared with the results from the maximum entropy spectral estimation, and the optimal order of this model can be determined from the eigen value's fluctuation of autocorrelation of background EEG. From the comparing results, this paper ensures that this method is possible to analyze the power spectrum of background EEG.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.158-161
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• 1989

This paper describes the AR model of EMG signal during maximum voluntary contraction. By comparing the AR coefficients and the reflection coefficients of the AR model with the median frequency of power spectrum, it if proved that muscle fatigue can be measured by the AR and the reflection coefficients. In the estimation procedure of AR model parameter, the auto-correlation method is superior to the covariance method, and it is determined that the optimal order is six. As the muscle becomes fatigue, the median frequency of power spectrum is declined, and the AR coefficient [$a_1$ ] and the reflection coefficient [$k_1$ ] are also decreased. Therefore the muscle fatigue can be measured by the AR parameter.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.8
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• pp.741-746
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• 2007

In this study, transfer path identification and output estimation are simulated by multi-dimension spectral analysis method (MDSA). Multi -input/single-output system give expression the vehicle suspension which each inputs are correlated reciprocally. In case of correlating with inputs, the system needs separating the each input signal by MDSA. Main simulations are about finding effective input by coherent output spectrum and selecting optimal input's number by multiple coherence function. Also, by shielding transfer path of each input, transfer path characteristic is identified in terms of overall integrated contribution level.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.211-218
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• 2003

Most structures are expected to deform beyond the limit of linearly elastic behavior when subjected to strong ground motion. Seismic evaluation of structure requires an estimation of the structural performance in terms of displacement demand imposed by earthquakes on the structure. Nonlinear response history analysis(NRHA) is the most rigorous procedure to compute seismic performance among various inelastic analysis methods. But nonlinear analysis procedures necessitate more practical and reliable tools for predicting seismic behavior of structures. This paper presents a nonlinear direct spectrum method(NDSM) to evaluate seismic performance of structures, without iterative computations, given by the structural initial elastic period and yield strength from the pushover analysis, especially for MDF(multi degree of freedom) system. The purpose of this paper is to investigate the accuracy and reliability of this method from a point of view of various earthquakes and structure parameters.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.600-612
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• 2014

In this paper, we consider the problem of spectrum sensing for advanced television systems committee (ATSC) digital television (DTV) signal detection. To exploit the cyclostationarity of the ATSC DTV signals, we employ spectral correlation density (SCD) as the decision statistic and propose an optimal detection algorithm. The major difficulty is in obtaining the probability distribution functions of the SCD. To overcome the difficulty, we probabilistically model the pilot frequency location and employ Gaussian approximation for the SCD distribution. Then, we obtain a practically implementable detection algorithm that outperforms the industry leading systems by 2-3 dB. We also propose various techniques that greatly reduce the system complexity with performance degradation by only a few tenths of decibels. Finally, we show how robust the system is to the estimation errors of the noise power spectral density level and the probability distribution of the pilot frequency location.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1189-1194
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• 2002

Acoustic intensity is usually estimated by the cross-spectrum of acoustic pressure at two adjacent micrphones. The cross-spectrum calculated by digital Fourier transform technique will unavoidally have leakage error since the period of signal will not be usually coincident with record length. Therefore, the acoustic intensity estimated by the conventional r]n analyzer will show distorted value. In this paper the expression of the Fourier transformed data of a harmonic signal is formulated when there is leakage error. The method to elimate the effect of leakage error from the contaminated data is also proposed. Some numerical examples show the validation of the proposed method.