• The Journal of the Acoustical Society of Korea
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• v.15 no.4
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• pp.50-57
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• 1996

In this paper, we proposed the method of optimal wavelet selection and wavelet expansion of AR(autoregressive) parameters by selected wavelet using F-test. A cost function is introduced as a wavelet selection method. Using this cost function, wavelets (D4 to D20) are tested to the synthesized signal. With this selected wavelet, we get the wavelet coefficients of AR parameters to both synthesized signal and real speech signal. To evaluate the proposed method, this wavelet based algorithm is compared with the Kalman filering algorithm. As a results, the proposed method shows a better performance by about 5-10dB than the Kalman filter.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.209-212
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• 2003

In this paper, we have analyzed a multiwavelet filter bank architecture which have several bases. The filter bank composed of multiwavelets bases is matrix-valued. Multiwavelets offer simultaneous orthogonality, symmetry, and short support, which is not possible for the scalar wavelet system, hence multiwavelet system can obtain excellent performance in signal analysis and compress. Also the multiwavelet differs from the scalar wavelet system in requiring two or more input streams to the multiwavelet filter bank. In this paper, we describe methods for obtaining such a input stream and how apply the actual data.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.670-679
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• 2003

This paper deals with application of wavelet transform, which is known to be good for time-frequency analysis, in order to detect the underwater transient signals embedded in ambient noise. A new detector of acoustic transient signals is presented. It combines two detection tools: wavelet analysis and higher-order statistics. Using both techniques, the detection of the transient signal is possible in low signal to noise ratio condition. The proposed algorithm uses the wavelet transform of a partition of the signal on frequency domain, and then higher-order statistics tests the Gaussian nature of the segments.

• The Korean Journal of Financial Studies
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• v.11 no.1
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• pp.1-36
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• 2005

한 시계열의 원래 관찰치가 본래 가지고 있는 정보를 하나도 잃지 않고 또한 손상시키지 않고 그대로 보존되며 계산이 용이하고, 뿐만 아니라 가능도함수나 비모수 추정함수를 계산함에 있어 수치적 불안정 잠재성이 존재하지 않도록 변환된 시계열을 얻을 수 있으면, 다시 말해 각종 통계량의 계산에 용이하게 적용 가능하되 원래 시계열이 보유하고 있는 모든 성질들은 추호도 손상시킴이 없이 이 시계열을 변환시킬 수 있는 변환방법이 존재한다면, 모수의 추정치와 검정통계량을 정확히 얻을 수 있을 것이다. 이와 같은 변환방법이 웨이브렛 변환이다. 이 변환은 푸리에 분석의 결점을 극복하되 후리에 변환이 적용되는 분야에는 거의 모두 적용 가능한 변환방법이다. 이 논문에서는 시계열의 웨이브렛 변환을 소개하고 이 변환이 재무시계열의 모형화에 한몫을 단단히 할 수 있다는 점을 밝히고자 한다. 그리고 웨이브렛 변환을 성공적으로 적용할 수 있는 주가과정을 하나의 예로 제시하여 웨이브렛 변환의 구체적 적용방법을 탐구하고자 한다. 웨이브렛의 주가 시계열의 적용방법의 한 예로 주가의 장기기억과정을 분석한다. 한국과 외국의 일별 주가지수의 수익률 시계열들이 장기기억과정을 따르는 시계열임이 발견되었다. 여러 형태의 웨이브들을 사용하여 검정하였는데 이 모두가 한결같이 주가지수가 장기기억성과정임을 지지하고 있다.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.1
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• pp.33-39
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• 1998

This paper discusses approximation modelling of discrete-time linear time-varying system(LTVS). The wavelet transform is considered as a tool for representing and approximating a LTVS. The joint time-frequency properties of wave analysis are appropriate for describing the LTVS. Simulation results is included to illustrate the potential application of the technique.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.221-232
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• 2012

The double-density discrete wavelet transform(DWT) is an improvement upon the critically sampled DWT with important additional properties. It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is overcomplete by a factor of two. Also, this transformation is nearly shift-invariant. But there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. Proposed method is a DWT that combines the double-density DWT and quincunx sampling, each of which has its own characteristics and advantages. Especially, the quincunx sampling treats the different directions more homogeneously. As a result, since proposed method can generate sub-images of multiple degrees rotated versions, this method provides an improved performance in image processing fields.

• Science of Emotion and Sensibility
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• v.7 no.2
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• pp.141-148
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• 2004

This paper proposed a new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in cA3 and weighted cDl. cA3 coefficients represent the voiced sound with low frequency and cDl coefficients represent the unvoiced sound with high frequency. From simulation results, it is demonstrated that the proposed algorithm improves SNR and MSE performance more than Wavelet transform and Wavelet packet transform does. Moreover, the reconstructed signals by the proposed algorithm resemble the original signal in terms of plosive sound, fricative sound and affricate sound but Wavelet transform and Wavelet packet transform reduce those sounds seriously.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.37-45
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• 1998

In this paper, the different frequency component and time informations from an EMI signal are extracted simultaneously using a wavelet transform and the results of transform in the time and frequency domain are analyzed. Frequencies are extracted from the EMI signal by performing the multiresolution analysis using the Daubechies-4 filter coefficients and the time information through the results of wavelet transform. We have tried the correlation analysis to evaluate the results of wavelet transform. We have chosen the optimal wavelet function for an object signal by comparing the transformed results of various wavelet functions and verified the simulation examples of waveform and harmonic analysis using a wavelet transform. We have proved the denoising effect to the EMI signal using the soft thresholding technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1283-1291
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• 2001

본 논문에서는 웨이브렛 영역에서 엔트로피 특징과 웨이브렛 모멘트의 융합에 의한 효율적인 영상기법을 제안한다. 엔트로피 특징은 밝기값의 국부적 변화도에 민감하고 밸리, 에지 등의 특징을 잘 검출한다. 이러한 특징을 주파수 대역별로 구해지는 웨이브렛 모멘트와 잘 융합하여 내용기반 영상검색에 효과적으로 적용하였다. 제안한 방법의 성능을 평가하기 위한 시험영상 DB로는 Corel Draw Photo 영상을 사용하였다. 실험 결과, 제안한 방법으로 구한 검색율이 기존의 웨이브렛 모멘트로 구한 검색율보다 11%이상 향상되어 매우 우수한 검색 성능을 보임을 확인하였다.

• Proceedings of the KAIS Fall Conference
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• 2000.10a
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• pp.203-207
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• 2000

최근 신호 처리 분야에서 많은 연구가 되고 있는 웨이브렛 변환을 적용하고, DSP(Digital Signal Processor)인 TMS320C31을 사용하여 고속 처리 가능한 하드웨어를 구현하였다. 그리고, 컴퓨터하고 일정한 통신 대역을 유지하고 다른 장치에 영향을 주지 안기 위해서 ISA 버스를 사용하였다. 여기서는 웨이브렛 변환과 푸리에 변환의 차이 및 필터뱅크에 대해서 알아보고, DSP를 이용하여 웨이브렛 변환을 시키는 하드웨어를 구현했다.