• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.827-832
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• 2003

There has been a number methods for the presentation of time-frequency analysis of non-stationary signal. In this paper, STFT(short time Fourier transform), wavelet transform, Wigner distribution, and higher order Wigner distribution are discussed in details with simulation signals. They are also applied to the analysis of the wave propagation of a semi finite beam. Wigner distribution and higher order Wigner distribution have good time-frewuency resolutions. Wavelet transform is required for impact analysis but should be applied carefully. STFT suffers from time-frequency resolutions. Each method is has its advantage and disadvantage depending on each application signals.

• 전자공학회논문지B
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• 제33B권8호
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• pp.50-59
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• 1996

In this paper, a new hierarchical motion estiamtion scheme using the wavelet transformed multi-resolution image layers is proposed. Compared with the full search motion estimation method, the existing hierarchical methods remarkably reduce the amount of the computation but their efficiencies are depreciated by the local minima problem. In order to solve the local minima problem, the multi-resolution image layers are composed using the wavelet transform and the number of layers participated in the motion estimation for a block is determined by considering of its low band energy and higher band energy on the first wavelet transformed layer. The ratio between higher band energy and low band energy of each block is evaluated and in the case of the blocks which include relatively large higher band energy, the motion estimation is carried out in the high resolution layer. Otherwise, all layers are used. The final motion vectors are obtained in the first wavelet transformed layer. So less bits for motion vectors are transmitted, and the decomposition of received image using inverse wavelet transform decreases the blocking effect.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.879-880
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• 2006

The subject of this paper is to recognize the stable state of EEG using wavelet transform and power spectrum analysis. An alpha wave, showed in stable state, is dominant wave for a human EEG and a beta wave displayed excited state. We decomposed EEG signal into an alpha wave and a beta wave in the process of wavelet transform. And we calculated each power spectrum of EEG signal, an alpha wave and a beta wave using Fast Fourier Transform. We recognized the stable state by making a comparison between power spectrum ratios respectively.

• 음성과학
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• 제5권1호
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• pp.23-33
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• 1999

Mallat has shown that, with a proper choice of wavelet function, the local maxima of wavelet transformed signal indicate a sharp variation in the signal. Since the glottal closure causes sharp discontinuities in the speech signal, dyadic wavelet transform can be useful for detecting abrupt change in the voiced sounds, i.e., epochs. In this paper, we investigate the glottal closure instants obtained from the wavelet analysis of speech signal and compare them with those obtained from the EGG signal. Then, we detect pitch period of speech signal on the basis of these results. Experimental results demonstrated that local maxima of wavelet transformed signal give accurate estimation of epoch and pitch periods of voiced sound obtained by the proposed algorithm also correspond to those from EGG well.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2005년도 전력전자학술대회 논문집
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• pp.476-478
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• 2005

This paper describes a method for the detection of shorted-turn in the cylindrical synchronous generator rotor windings based on the discrete wavelet transform. Multi-resolution analysis(MRA) based on discrete wavelet transform provides a set of decomposed signals in independent frequency bands. In the proposed method, shorted-turn detection in rotor windings is based on the decomposition of the rotor currents, where wavelet coefficients of these signals have been extracted. Comparing these extracted coefficients is used for diagnosing the healthy machine from faulty machine. Experimental results show the effectiveness of the proposed method for shorted-turn detection in the cylindrical synchronous generator rotor windings.

• 한국통신학회논문지
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• 제21권7호
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• pp.1654-1667
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• 1996

The conventional fractal image compression methods have high computational complexity at encoding reduce PSNR at low bit rate and havehighly visible blocking effects in a reconstructed image. In this paper we propose a fractal image compression method based on disctete wavelet transform domain, which takes the absolute value of discrete wavelet transform coefficient, and assembles the discrete wavelet tranform coefficients of different highpass subbands corresponding to the same spatial block and then applies "0" encoding according to the energy of each range blocks. The proposed method improved PSNR at low bit rate and reduced computational complexity at encoding distinctly. Also, this method can achieve a blockless reconstructed image and perform hierarchical decoding without recursive constractive transformation. Computer simulations with several test images show that the proposed method shows better performance than convnetional fractal coding methods for encoding still pictures. pictures.

• 대한전기학회논문지:전력기술부문A
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• 제51권3호
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• pp.134-142
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• 2002

This paper presents a new method for the protective relaying scheme in power transformer using wavelet based neural networks. This approach is as fellows. After approximation and detail information is extracted by daub wavelet transform from differential current of power transformer, the former is used for obtaining the rate of differential currents and restrain currents, the latter used as the input of artificial neural networks to avoid the Hiss-operation in over-exciting state and magnetizing inrush state of power transformer. The simulation of EMTP with respect to different faults, inrush conditions and over-exciting conditions in power transformer have been conducted, and the results preyed that the proposed method is able to discriminate magnetizing inrush states, over-exciting stales and internal faults.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2327-2329
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• 2000

This paper addresses the use of a nonlinear modeling procedure which construct a wavelet-based fuzzy model using genetic algorithm. A fuzzy inference system has the functional equivalence with a wavelet transform. Therefore, a wavelet-based fuzzy model using GA inherits the advantage of wavelet transform. Hereby, its performance is promoted. By help of the ability of GA to search the optimum globally, parameters of wavelet transform is determined closely to the optimal point. The feasibility of the proposed fuzzy model is proved by modelling a highly nonlinear function and comparing it with previous research.

• 전자공학회논문지S
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• 제35S권5호
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• pp.59-67
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• 1998

This paper propose a new vector-quantizer design method for coefficients of wavelet transformed images. In conventional wavelet transform, it is quite often to employ wavelet transformed coefficients, not containing images to be encoded, as training sequences for designing a vector-quantizer. This method has a serious drawback ; it is not known how to find a proper set of training images. This paper investigates characteristics of images that should be considered in the design of vector-quantizers for wavelet transformed images. Besides the statistical parameters such as correlation and standard deviation, edge components are shown to characterise wavelet transform images. Training sequences established in accordance with the above knowledge are used in the design of quantizers having guaranteed range of applicable images. Results of computer simulations are shown to demonstrate the effectiveness of the proposed method.

• 전자공학회논문지B
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• 제32B권9호
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• pp.1188-1197
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• 1995

This paper describes an algorithm that reduces computational requirement of the Kalman filter and estimates the signal efficiently. The reference signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be smaller than that in the time domain. In the wavelet transform domain the autocorrelation matrix is nearly diagonal. Therefore, the transformed signal can be decomposed each orthogonal elements. The Kalman filter can be applied to each orthogonal elements and computational requirement is reduced. The possibility of applying the parallel Kalman filter was verified through the theory and simulation. The eigenvalue spread in the wavelet transform domain is smaller 8.35 times than that in the time domain and the computational requirement is reduced from 1.4 times to 2. 93 times than that of the conventional Kalman filter.