• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.199-209
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• 2003

When a sampling theorem holds in wavelet subspaces, sampling expansions can be a good approximation to projection expansions. Even when the sampling theorem does not hold, the scaling function series with the usual coefficients replaced by sampled function values may also be a good approximation to the projection. We refer to such series as hybrid sampling series. For this series, we shall investigate the local convergence and analyze Gibbs phenomenon.

• Journal of information and communication convergence engineering
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• v.2 no.4
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• pp.251-255
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• 2004

In this paper, we present a watermarking scheme based on the DWT (Discrete Wavelet Transform) and the ANN (Artificial Neural Network) to ensure the copyright protection of the digital images. The problem to embed watermark is not clear to select important coefficient in the watermarking. We used the RBF (Radial-Basis Function) to solve the problem. We didn't apply the whole wavelet coefficients, but applied to only the wavelet coefficients in the selected node. Using the ANN, although even the watermark casting process and watermark verification process are in public, nobody knows the location of embedding watermark except of authorized user. As the result, the watermark is good at the strength test-filtering, geometric transform and etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.203-206
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• 2008

기존의 대표적인 디지털 통신방식으로 주파수 편이 변조(FSK: frequency shift keying), 위상 편이 변조(PSK: phase shift keying), 진폭 편이 변조(ASK: amplitude shift keying) 방식들이 있다. 본 논문에서는 2진 정합필터를 이용하여 웨이브릿 편이변조 신호를 복원하는 알고리즘을 제안한다. 웨이브릿 편이 변조 시스템은 스케일링 함수(scaling function)와 웨이브릿(wavelet)을 이용한다. 스케일링 함수를 1로, 웨이브릿 함수를 0으로 할당하여 2진 데이터를 변조한다. 기존의 웨이브릿 편이 변조 시스템에서는 복원을 위해 후처리가 필요하였다. 된 논문에서는 2진정합필터를 이용하여 복원하므로, 별도의 후처리 과정 없이 복원을 가능하게 하였다. 모의실험 결과 제안한 알고리즘이 타당함을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.16-22
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• 2007

This study proposes a new wavelet watermark technique based on the Linear Bit Expansion. To ensure the security of the watermark, enlarged watermark by applying linear bit expansion is inserted in a given intensity to a low frequency subband of the image which is wavelet transformed after the Arnold Transformation. When detecting the presence of watermart F norm function is applied unlike the existing methods. The experiment results verify that the proposed watermarking technique has outstanding quality in regards to fidelity and robustness.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.257-261
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• 2005

The helicopter system is non-linear and complex. Futhermore, because of absence of accurate mathematical model, it is difficult accurately to control its attitude. therefore, we propose a WAVENET control technique to control efficiently its elevation angle and azimuth one. Wavelet neural network(WAVENET) can construct systematically initial neural network as applying wavelet theory to feedforward network. It is proved through computer simulation that WAVENET has more excellent approximation capability than existing neural network. The simulation results using MATLAB are introduced.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2956-2958
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• 1999

The classical solution to the noise removal problem is the Wiener filter, which utilizes the second-order statistics of the Fourier decomposition. We discuss a Bayesian formalism which gives rise to a type of wavelet threshold estimation in non-parametric regression. A prior distribution is imposed on the wavelet coefficients of the unknown response function, designed to capture the sparseness of wavelet expansion common to most application. For the prior specified, the posterior median yields a thresholding procedure

• Communications of the Korean Mathematical Society
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• v.15 no.1
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• pp.183-195
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• 2000

High accuracy Wavelet basis $\beta$ is constructed in [2]. We derive a condition for smoothness of the basis function $\beta$(x).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.29-37
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the diagnosis of grinding conditions in grinding process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. STD11 workpiece was 85 times of machined pieces cut by the WA wheel and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At dressing time, the approximation signals were slowly increased and 45 machined times noticed dressing time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.1063-1066
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.78-85
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• 2002

The wavelet transform is a popular tool fer studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.