• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.96-98
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• 2006

A new ex-situ model to diagnose a plasma processing equipment was presented. The model was constructed by combining wavelet, scanning electron microscope, ex-situ measurement of etching profile, and neural network. The diagnosis technique was applied to a tungsten etching process, conducted in a $SF_6$ helicon plasma. The wavelet was used to characterize detailed variations of plasma-etched surface. The diagnosis model was constructed with the vertical wavelet component. For comparison, a conventional model was built by using the estimated profile data. Compared to the conventional model, the wavelet-based model, demonstrated a much improved diagnosis.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.173-174
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• 2008

Wavelet transform is a new method for power system analysis. On the basis of extensive investigation, optimal mother wavelets for the detection of leakage current are chosen. The recommended mother wavelet is 'Daubechies 4' wavelet. This paper proposes a technique for modeling toe finding point of leakage current in distribution system using wavelet transform and EMTP MODELS.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.246-249
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• 2009

Due to the additive white Gaussian noise (AWGN), images are often corrupted. In recent days, Bayesian estimation techniques to recover noisy images in the wavelet domain have been studied. The probability density function (PDF) of an image in wavelet domain can be described using highly-sharp head and long-tailed shapes. If a priori probability density function having the above properties would be applied well adaptively, better results could be obtained. There were some frequently proposed PDFs such as Gaussian, Laplace distributions, and so on. These functions model the wavelet coefficients satisfactorily and have its own of characteristics. In this paper, mixture distributions of Gaussian and Laplace distribution are proposed, which attempt to corporate these distributions' merits. Such mixture model will be used to remove the noise in images by adopting Maximum a Posteriori (MAP) estimation method. With respect to visual quality, numerical performance and computational complexity, the proposed technique gained better results.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.194-200
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• 1999

Localized damage to a structure affects its dynamic properties, and much work has been undertaken investigating the variation of natural frequencies, damping ratios and mode shapes. This paper presents a technique based on wavelet transform to detect the existences and locations of structural damages. The procedure operates solely on the mode shape from the damaged structure, and does not require a priori knowledge of the undamaged structure. The procedure is developed using a 32-story shear building model. Applying wavelet transform to the mode shape successfully identifies the location of damage. The procedure is best suited to the mode shape obtained from the fundamental natural frequency. The wavelet coefficients from the higher mode shapes can be used to verify the location of damage, but they are not as sensitive as the wavelet coefficients of the lower mode shapes.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.333-334
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• 2006

In this study, information compression based on the wavelet technique is described. The principle of signal or image compression is performed by optimization of quantization, that is the bit allocation taking advantage of their energy concentration in low frequency components. The wavelet transform is one of frequency decomposition, such as the discrete cosine transform or sub-band filtering, and it is also implemented as a filter bank. Wavelet transform with use of spatially localized basis function can reduce several drawbacks in conventional methods. The benifit of wavelet based compression method is described as comparing the transform method to another ones.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.284-287
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• 2003

A wavelet transform which is presented as a new technique of signal processing field decompose input signals into subsignals for expressing them in different resolutions and into detail signals for expressing the remaining signals. And the signals obtained from the progress include the information about input signals at the same time and scale. And when two wavelet bases are designed to form Hilbert transform pair, wavelet Pair show superior performance than the existing DWT in data detection of pulse type. Therefore in this paper, we detected position of impulse noise by using two dyadic wavelet bases which are designed by truncated coefficient vector.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2040-2042
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• 2003

In this paper, we propose a new method about wavelet-based fuzzy modeling using a DNA coding method. DNA coding techniques is known that expression of knowledge is various than Genetic Algorithm(GA) usually by made optimization technique because done base in structure of biologic DNA and optimization performance is superior. The reposed method make fuzzy system model in wavelet transform and equivalence relation after identification with coefficient of wavelet transform using a DNA coding techniques. Also, can get fuzzy model effectively of nonlinear system using advantage of strong wavelet transform about function that have sudden change. In this paper, in order to demonstrate the superiority of the proposed method compared with GA.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2365-2370
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• 2008

In this paper, applications of wavelet neural network controller to position control of nonlinear system are considered. Wavelet neural network is used in the objectives which improve the efficiency of LQR controllers. It is possible to make unstable nonlinear systems stable by using LQR(Linear Quadratic Regulator) technique. And, in order to be adapted to disturbance effectively in this system it uses wavelet neural network controller. Applying this method to the position control of nonlinear system, its usefulness is verified from the results of experiment.

• ETRI Journal
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• v.44 no.5
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• pp.826-836
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• 2022

Signal decomposition is a computational technique that dissects a signal into its constituent components, providing supplementary information. In this study, the capability of two common signal decomposition techniques, including wavelet-based and empirical mode decomposition, on preterm birth classification was investigated. Ten time-domain features were extracted from the constituent components of electrohysterogram (EHG) signals, including EHG subbands and EHG intrinsic mode functions, and employed for preterm birth classification. Preterm birth classification and anticipation are crucial tasks that can help reduce preterm birth complications. The computational results show that the preterm birth classification obtained using wavelet-based decomposition is superior. This, therefore, implies that EHG subbands decomposed through wavelet-based decomposition provide more applicable information for preterm birth classification. Furthermore, an accuracy of 0.9776 and a specificity of 0.9978, the best performance on preterm birth classification among state-of-the-art signal processing techniques, were obtained using the time-domain features of EHG subbands.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.861-869
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• 2003

The rapid growth of multimedia network systems has caused overflowing illegal copies of digital contents. Among digital contents, watermarking technique can be used to protect ownership about the image. Copyright protection involves the authentication of image ownership and the identification of illegal copies of image. In this paper, a new digital watermarking technique using HVS and adaptive scale factor based on the wavelet transform is proposed to use the binary image watermark. The original image is decomposed by 3-level wavelet transform. It is embedded to baseband and high frequency band. The embedding in the baseband is considered robustness, the embedding in the high frequency band is concerned about HVS and invisibility. The watermarking of a visually recognizable binary image used the HVS and random permutation to protect the copyright. From the experimental results, we confirm that the proposed technique is strong to various attacks such as joint photographic experts ground(JPEG) compression, cropping, collusion, and inversion of lines.