• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.969-971
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• 1999

Wavelet analysis is applying to many fields such as the time-frequency localization of a time series and a time varying data. In this paper, a statistical testing based Wavelet power spectrum analysis for the stationary Nino3 Sea Surface Temperature(SST) data was executed. Specially, the 95% confidence level for SST was effective in searching the periods of El-Nino using various wavelet basis functions.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.521-524
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• 1999

In spite of advances in image resolution and film contrast, check screen/film mammography remains one of diagnostic imaging modality where the image interpretation is very difficult. For the enhancement of film mammography, in this paper, dyadic wavelet transform is introduced. An unsharp masking technique is proposed and performed in wavelet domain. In addition, simple nonlinear enhancement and a denosing stage that preserves edges using wavelet shrinkage are computed into this technique. In this paper. we propose a new method for the gain setting of nonlinear enhancement and show result and comparison.

• Journal of Industrial Technology
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• v.19
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• pp.403-408
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• 1999

An efficient method is developed for classifying fingerprint data based on 2-D discrete wavelet transform. Fingerprint data is first converted to a binary image. Then a multi-level 2-D wavelet transform is performed. Vertical and horizontal subbands of the transformed data show typical energy distribution patterns relevant to the fingerprint categories. The proposed method with moderate level of wavelet transform is successful in classifying fingerprints into 5 different types. Finer classification is possible by higher frequency subbands and closer analysis of energy distribution.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.635-637
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• 1998

Based on wavelet theory, the new notion of wavelet networks is proposed as alternative to feedforward neural networks for approximating arbitrary nonlinear functions. An algorithm presented in this paper trains coefficients of wavelet. i.e., translations and scaling., and then learns weights with the wavelet coefficients. And experimental results are reported.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.225-230
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• 1997

Discrete Wavelet Transforms (DWTs) are recent mathematics, and begin to be used in various fields. The wavelet transform can be used to compress the signal and image due to its inherent properties. We applied the wavelet transform compression and reconstruction to the neutron cross section data. Numerical tests illustrate that tile signal compression using wavelet is very effective to reduce the data saving spaces.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.126-129
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• 2000

In order to approximate a nonlinear function, wavelet neural networks combining wavelet theory and neural networks have been proposed as an alterantive to coventional multi-layered neural networks. Wavelet neural networks provide better approximating performance than conventional neural networks. In this paper, an effective method to construct an optimal wavelet neural network is proposed using genetic algorithm. This is verified through experimental results.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1918-1920
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• 2000

In this paper, acoustic signals in GIS were analyzed by using wavelet transform and FFT to distinguish sound source caused by collision of particles and partial discharges. As a result, the analysis using wavelet transform was more accurate than that using FFT. Therefore, wavelet transform was useful technique to analyze the acoustic signals in GIS.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.592-594
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• 2003

이 논문에서는 wavelet과 sobel filter를 사용하여 영상의 객관적인 평가 점수를 계산하는 새로운 기법을 제안한다. 이 기법은 orthogonal wavelet 변환을 기초로 하고 있으며 원본 영상과 처리된 영상 데이터가 모두 가용하다는 것을 전제로 한다. Wavelet을 이용해 주파수에 따라 분할된 영상 정보를 이용해 각각의 부영역 별 차영상을 획득하고 이 획득된 영상의 에너지를 이용해 화질 평가 수치를 계산한다. 부영역 별로 획득된 영상은 일정한 크기의 블록으로 분할되어 동일한 블록 내에서 가용한 영상의 특징에 관한 정보(contrast, edge 영역의 분포 정도) 벡터와 내적하여 새로운 특징 벡터로 사용되고, 이 특징 벡터의 가중치를 최적화하여 높은 상관도의 화질평가 점수를 산출하게 된다.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.379-386
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• 2008

In this paper, the choice of a primary resolution and wavelet basis functions are introduced under random or irregular design points of which the sample size is free of a power of two. Most wavelet methods have used the number of the points as the primary resolution. However, it turns out that a proper primary resolution is much affected by the shape of an unknown function. The proposed methods are illustrated by some simulations.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.419-426
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• 2009

In expansion of function by special basis functions, properties of expansion kernel are very important. In the Fourier series, the series are expressed by the convolution with Dirichlet kernel. We investigate some of properties of kernel in wavelet expansions both in one and higher dimensions.