• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.559-568
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• 2017

Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be employed to extract the harmonic or inter-harmonic components of a distorted electric voltage/current signal. In the MP iterations, the method extracts harmonic/inter-harmonic components in order according to the spectrum peak. The Fast Fourier Transform (FFT) and nonlinear optimization techniques are used in the decomposition to realize fast and accurate estimation of the parameters. First, the frequency estimation value corresponding to the maxim spectrum peak in the present residual is obtained, and the phase corresponding to this frequency is searched in discrete sinusoids dictionary. Then the frequency and phase estimations are taken as initial values of the unknown parameters for Nelder-Mead to acquire the optimized parameters. Finally, the duration time of the disturbance is determined by comparing the inner products, and the amplitude is achieved according to the matching expression of the harmonic or inter-harmonic. Simulations and actual signal tests are performed to illustrate the effectiveness and feasibility of the proposed method.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.64-74
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• 2014

The primary and ambient signal decomposition of a stereo sound is a key step to the stereo upmix. The principal component analysis (PCA) is one of the most widely used methods of primary-ambient signal decomposition. However, previous PCA-based decomposition algorithms assume that stereo sound sources are only amplitude-panned without any consideration of phase difference. So it occurs some performance degradation in case of live recorded stereo sound. In this paper, we propose a new PCA-based stereo decomposition algorithm that can consider the phase difference between the channel signals. The proposed algorithm overcomes limitation of conventional signal model using PCA with phase alignment. The phase alignment is realized by using inter-channel phase difference (IPD) which is widely used in parametric stereo coding. Moreover, Enhanced Modified PCA(EMPCA) is combined to solve the problem of conventional PCA caused by Primary to Ambient energy Ratio(PAR) and panning angle dependency. The simulation results are presented to show the improvements of the proposed algorithm.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.1
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• pp.107-114
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• 1999

In many applications (e,g., identification of non-destructive testing signal and biomedical signal and multiscale analysis of image), it is of interest to analyze and identify phenomena occurring at the different scales. The recently introduced wave let transforms provide a time-scale decomposition of signals that offers the possibility of such signals. However, there is no corresponding statistical properties to development of multiscale statistical signal processing. In this paper, we derive such properties of random signals in wavelet domain.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.193-201
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• 2022

SOQPSK-TG is a modulated signal for aircraft telemetry with excellent frequency efficiency and power efficiency. In this paper, the phase waveform of the partial response SOQPSK-TG modulation is linearly approximated and modeled as a full response double duobinary SOQPSK (SOQPSK-DD) signal. And using the XTCQM method and the Laurent decomposition method, the SOQPSK-DD signal was approximated as OQPSK having linear pulse waveforms, and the results of the two methods were proved to be the same. In addition, it was confirmed that the Laurent decomposition waveform of the SOQPSK-DD signal approximates the Laurent decomposition waveform of the original SOQPSK-TG signal. And it was shown that the decision feedback IQ-detector, which applied the Laurent decomposition waveform of SOQPSK-DD to the detection filter, exhibits almost the same performance even with a simpler waveform than before.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.89-92
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• 2014

This paper presents a secure and blind adaptive audio watermarking algorithm based on Empirical Mode Decomposition (EMD). The audio signal is divided into frames and each one is decomposed adaptively, by EMD, into several Intrinsic Mode Functions (IMFs). The watermark and the synchronization codes are then embedded into the extrema of the last IMF. The experimental results show that the proposed method has good imperceptibility and robustness against signal processing attacks.

• Geosystem Engineering
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• v.21 no.5
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• pp.251-261
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• 2018

With the urbanization in recent years, the power line interference noise in electromagnetic signal is increasing day by day, and has gradually become an unavoidable component of noises in magnetotelluric signal detection. Therefore, a kind of power line interference noise elimination method based on independent component analysis in wavelet domain for magnetotelluric signal is put forward in this paper. The method first uses wavelet decomposition to change single-channel signal into multi-channel signal, and then takes advantage of blind source separation principle of independent component analysis to eliminate power line interference noise. There is no need to choose the layer number of wavelet decomposition and the wavelet base of wavelet decomposition according to the observed signal. On the treatment effect, it is better than the previous power line interference removal method based on independent component analysis. Through the de-noising processing to actual magnetotelluric measuring data, it is shown that this method makes both the apparent resistivity curve near 50 Hz and the phase curve near 50 Hz become smoother and steadier than before processing, i.e., it effectively eliminates the power line interference noise.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4A
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• pp.507-515
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• 2008

In this study, a method predicting the displacement response of structures from the measured dynamic strain signal is proposed by using mode decomposition technique. Evaluation of bridge stability is normally focused on the bridge completed. However, dynamic loadings including wind and seismic loadings could be exerted to the bridge under construction. In order to examine the bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. Because it may be not easy for the displacement response to be acquired directly on site, an indirect method to predict the displacement response is needed. Thus, as an alternative for predicting the displacement response indirectly, the conversion of the measured strain signal into the displacement response is suggested, while the measured strain signal can be obtained using fiber optic Bragg-grating (FBG) sensors. As previous studies on the prediction of displacement response by using the FBG sensors, the static displacement has been mainly predicted. For predicting the dynamic displacement, it has been known that the measured strain signal includes higher modes and then the predicted dynamic displacement can be inherently contaminated by broad-band noises. To overcome such problem, a mode decomposition technique was used. Mode decomposition technique estimates the displacement response of each mode with mode shape estimated to use POD from strain signal and with the measured strain signal decomposed into mode by EMD. This is a method estimating the total displacement response combined with the each displacement response about the major mode of the structure. In order to examine the mode decomposition technique suggested in this study model experiment was performed.

• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.395-402
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• 1995

The intravoxel spin phases in magnetic resonance imaging (MRI) usually vary due to susceptibility differences of materials to be imaged. The phase variation in the voxel results in a reduction of the signal intensity. This signal intensity reduction is known as the susceptibility effect in MRI and has been studied extensively. In this paper, a new spectral decomposition technique Is proposed and the signal change due to the susceptibility effect can be analyzed. A pulse sequence for the spectral decomposition of the susceptibility was developed and applied to susceptibility imaging of venous blood possessing paramagnetic properties. The computer simulations and their corresponding experimental results obtained using both a phantom and human volunteers are reported. Key words : susceptibility effect in MRI : spectral decomposition of susceptibility effect.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.319-330
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• 2006

A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.

• Journal of the Korean Solar Energy Society
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• v.32 no.6
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• pp.29-36
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• 2012

The existing solar tracking sensor for 2 axial control system to trace latitude and longitude is made of four phototransistor. The phototransistor-making is difficult and it's manufacturing is more high-priced than a wide use phototransistor because they have to the same characteristics of each phototransistor output signal. This paper described the algorithm for supplement these weakness. The algorithm applied to signal normalizing method and vector decomposition law. The deviations of each a wide use phototransistor output signal are resolved by signal normalizing method and it is able to make a solar tracking sensor using three phototransistor by vector decomposition law. Therefore, in this paper, it is reduced the number of phototransistor that is composed of solar tracking sensor and possible to use a wide use phototransistor by the proposed algorithm.