• Journal of Korea Planning Association
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• v.54 no.3
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• pp.63-74
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• 2019

Korean government has implemented policies to strengthen the competitiveness of small and medium sized cities. However, since it is often difficult to enhance the competitiveness through individual projects, many local governments in metropolitan areas are working together to pursue local growth. On the other hand, small and medium sized cities that are not included in metropolitan areas due to their spatial limitations have difficulties in implementing effective growth policies. Given this background, the purpose of this study is to identify the functional correlation based on urban interactions and develop functional econometric model for the economic growth of small and medium sized cities. This study uses spatial econometrics models and functional weight matrix to identify the effects of functional networks on small and medium sized cities. The results show the effect of functional networks on the growth of small and medium sized cities and provide policy implications for regional spatial planning that addresses effective management of small and medium sized cities.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4E
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• pp.39-44
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• 2001

We investigate the numerical instability of linear prediction for discrete harmonic spectra of audio signals. It is identified that the eigenvalue spread is very large when discrete harmonic spectra are confined only in a lower part of the entire signal bandwidth. A simple method that redefines the sampling frequency and associate harmonic frequencies is proposed to improve the numerical stability. Simulation results using real audio signals indicate its superior stabilizing ability and improved accuracy in the discrete spectral estimation for both LP and DAP.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.149-158
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• 2015

This paper proposes a subband filtering technique to the MUSIC and the ESPRIT algorithm for estimating the magnitude and frequency of the harmonics of power signal. In proposed method, the input power signal is decomposed to the odd harmonics and the even harmonics respectively by the filter bank system. The amplitude and the frequency estimation of the decomposed harmonics are carried out using the MUSIC and the ESPRIT method. Subband filtering can reduce the autocorrelation matrix size of input data, and spectrum leakage between adjacent harmonics. Therefore, this subband technique has advantage in computational cost and estimation accuracy compared to fullband MUSIC and ESPRIT. To demonstrate the performance of the method, computer simulations are performed to the synthesized input signal, and experiment results are compared in subband and fullband cases.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.319-329
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• 1998

In the linear regression model with an autocorrelated disturbances, the Cochrane-Orcutt estimator (COE) is a well known alternative to the Generalized Least Squares estimator (GLSE). The efficiency of COE has been studied empirically in a Monte Carlo study when the unknown parameters are estimated by maximum likelihood method. In this paper, it is theoretically proved that the COE is shown to be inferior to the GLSE. The comparisons are based on the difference of corresponding information matrices or the ratio of their determinants.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.644-646
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• 1998

The main drawback of filtered-X LMS(FXLMS) algorithm for the ANC of broadband noises is its low convergence speed when the filtered reference signals are strongly correlated, producing a large eigenvalue spread in correlation matrix. This correlation can be caused either by autocorrelation of the signals of the reference sensors, or by coupling between the error path which introduces intercorrelation in the filtered reference signals. In this paper, we introduce a transform domain FXLMS(TD-FXLMS) algorithm that has a high convergence speed by orthogonal transform's decorrelation properties.

• ETRI Journal
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• v.32 no.3
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• pp.460-463
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• 2010

This letter proposes an energy-detection-based non-data-aided weighted non-coherent receiver (NDA-WNCR) scheme for impulse radio ultra-wideband (IR-UWB) pulse-position modulated signals. Compared to the conventional WNCR, the optimal weights of the proposed NDA-WNCR are tremendously simplified as the maximum eigenvector of the IR-UWB signal energy sample autocorrelation matrix. The NDA-WNCR serves to blindly obtain the optimal weights and entirely circumvent the transmission of training symbols or channel estimation in practice. Analysis and simulation results verify that the bit error rate (BER) performance of the NDA-WNCR closely approaches the ideal BER of the conventional WNCRs.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.305-316
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• 1994

All physical data in the real world are nonstationary signals that have the time varying statistical characteristics. Although few algorithms suitable to process the nonstationary signals have ever been suggested, these are treated the nonstationary signals under the assumption that the nonstationary signal is a piece-wise stationary signal. Recently, statistical analysis algorithms for the nonstationary signal have concentrated so much interest. In this paper, nonstationary EMG signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be more smaller than that in the time domain. Then the model in the wavelet transform domain and an algorithm to estimate the model parameters are suggested. Also, an test signal generated by a white gaussian noise and the EMG signal are identified, and the algorithm performance is considered in the sense of the mean square error and the evaluation parameters.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1327-1329
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• 1996

This paper presents an active noise control (ANC) algorithm using orthogonalization property of Walsh transform. Conventional ANC algorithm known as filtered-x LMS(FXL) algorithm has a problem of decreasing convergence speed in FIR adaptive filters operating in colored noise environments. Walsh transform decompose an input signal into a set of N uncorrelated components and reduce eigenvalue spread of autocorrelation matrix of input sequences. Computer simulations show that proposed (FXW) algorithm is superier to FXL in convergence speed.

• Structural Engineering and Mechanics
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• v.59 no.1
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• pp.187-207
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• 2016

Practical ambient excitations of engineering structures usually do not comply with the stationary-white-noise assumption in traditional operational modal analysis methods due to heavy traffic, wind guests, and other disturbances. In order to eliminate spurious modes induced by non-white noise inputs, the improved stochastic subspace identification based on a delay index is proposed in this paper for a representative kind of stationary non-white noise ambient excitations, which have nonzero autocorrelation values near the vertical axis. It relaxes the stationary-white-noise assumption of inputs by avoiding corresponding unqualified elements in the Hankel matrix. Details of the improved stochastic subspace identification algorithms and determination of the delay index are discussed. Numerical simulations on a four-story frame and laboratory vibration experiments on a simply supported beam have demonstrated the accuracy and reliability of the proposed method in eliminating spurious modes under non-white noise ambient excitations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.85-93
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• 2007

In case that multichannel blind deconvolution (MBD) applies to signals of which autocorrelation has a high level, separated signals are temporally whitened by diagonal elements of a separation filter matrix. In order to reduce this distortion, the algorithms, which are based on either constraining diagonal elements of a separation filter matrix or estimating a separation filter matrix by using linear prediction residual signals, are presented. Still, some problems are generated in these methods, when we separate reverberation of signals themselves or interference signals from mixed signals. To solve these problems, this paper proposes the multichannel blind deconvolution method which divides processing procedure into the stage to separate interference signals and the stage to eliminate a reverberation of signals themselves. In simulation results, we confirm that the proposed algorithm can solve the problems.