• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.468-475
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• 2018

In medical ultrasound imaging, frequency-dependent attenuation downshifts and reduces a center frequency and a frequency bandwidth of received echo signals, respectively. This causes considerable errors in quadrature demodulation (QDM), result in lowering signal-to-noise ratio (SNR) and contrast resolution (CR). To address this problem, adaptive dynamic QDM (ADQDM) that estimates center frequencies along depth was introduced. However, the ADQDM often fails when imaging regions contain hypoechoic regions. In this paper, we introduce a valid region-based ADQDM (VR-ADQDM) method to reject the misestimated center frequencies to further improve SNR and CR. The valid regions are regions where the center frequency decreases monotonically along depth. In addition, as a low-pass filter of QDM, Gaussian wavelet based dynamic filtering was adopted. From the phantom experiments, average SNR improvements of the ADQDM and the VR-ADQDM over the traditional QDM were 1.22 and 5.27 dB, respectively, and the corresponding maximum SNR improvements were 2.56 and 10.58 dB. The contrast resolution of the VR-ADQDM was also improved by 0.68 compared to that of the ADQDM. Similar results were obtained from in vivo experiments. These results indicate that the proposed method would offer promises for imaging technically-difficult patients due to its capability in improving SNR and CR.

• Journal of the Korean Society of Propulsion Engineers
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• v.2 no.2
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• pp.88-98
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• 1998

A waveform for shock response spectrum test on a shaker is synthesized using wavelets such that a specified shock response spectrum of a test profile is achieved. The parameters of a wavelet are center frequency, amplitude, number of half cycles, delay and polarity. The amplitude of each wavelet component is iteratively adjusted so a specified shock response spectrum is matched. The waveform so synthesized is regarded as a reference acceleration waveform for a shaker shock response spectrum test. The author proposes the use of a long duration and low peak waveform. The usefulness of this approach is illustrated with some examples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.535-539
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• 2008

With the advancement which development and information communication of the computer is quick about lower with multimedia technical diffusion of network base the necessity the use of the digital image technique which is various regarding the protection of sharp increasing multimedia contents raised its head in the social whole. The copyright protection against a multimedia data hazard the authentication techniques it will be able to confirm the content authentication, ownership authentication, illegal copy of the image which stands is demanded. confronts to the water marking technique of existing and the researches the fact that against a picture is most. In this paper, It does not damage the video data. As inserts copyright information and it protects the copyright. It is with a copyright protection which leads the wavelet transform which is a watermark of frequency base from visual system viewpoint in the human being center with it proposes the watermarking technique against a forgery prevention.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.39-48
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• 2005

This paper proposes a novel approach to recognize nine kinds of motion for a multifunction myoelectric hand, acquiring four channel EMG signals from electrodes placed on the forearm. To analyze EMG with properties of nonstationary signal, time-frequency features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. From experimental results, we show that the proposed method enhances the recognition accuracy, and makes it possible to implement a real-time pattern recognition.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.308-315
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• 2009

Because the attenuation of AE signal in composite materials is relatively higher than that of metallic materials, it is required to develop a damage assessment technique less affected by the attenuation property of composite materials in order to use AE sensing as a damage detection method. In the signal processing procedure, it is profitable to use the leading wave that arrives first because the leading wave is less influenced by the boundary conditions. Using wavelet transform, we investigated the frequency characteristics of impact induced AE signals focused on the leading wave in advance and chose the key factors to discriminate the damaged condition quantitatively. In this research, we established a damage assessment technique using the sharing percentage of the wavelet detail components of AE signal, and conducted a low-velocity impact test on composite laminates to confirm the feasibility of the proposed signal processing method.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.144-154
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• 1999

The binomial sequences are family of orthogonal sequences that can be generated with remarkable simplicity-no multiplications are necessary. This paper introduces a class of non-recursive multidimensional filters for frequency-selective image processing without multiplication operations. The magnitude responses are narrow-band. approximately gaussian-shaped with center frequencies which can be positioned to yield low-pass. band-pass. or high-pass filtering. Algorithms for the efficient implementation of these filters in software or in hardware are described. Also. we show that the binomial QMFs are the maximally flat magnitude square Perfect Reconstruction paraunitary filters with good compression capability and these are shown to be wavelet filters as well. In wavelet transform the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal direction and maintains constant the number of pixels required to describe the images. An efficient perfect reconstruction binomial QMF-Wavelet signal decomposition structure is proposed. The technique provides a set of filter solutions with very good amplitude responses and band split. The proposed binomial QMF-filter structure is efficient, simple to implement on VLSl. and suitable for multi-resolution signal decomposition and coding applications.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.143-147
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• 2007

This paper proposes a new watermarking scheme in which a logo watermark is embedded into the discrete wavelet transform (DWT) domain of the original image using exact radial basis function neural networks (RBF). RBF will learn the characteristics of the image, and then watermark is embedded and extracted by the trained RBF. A watermark is added to the coefficients at the low frequency band of the DWT of an image and a watermark is embedded into the DWT domain using the trained RBF. The trained RBF also used in watermark extracting process. Experimental results show that the proposed method has good imperceptibility and high robustness to common image processing attacks.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.137-141
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• 2006

The purpose of GPS structural vibration monitoring is to obtain information on the frequency and amplitude of vibrations based on GPS observations that are often affected by various errors. Filters are frequently used to improve GPS accuracy and to retrieve vibration signals from GPS observational series. This paper studies the performances of four commonly used filters, i.e., Vondrak, wavelet, adaptive FIR and Kalman filters, for such applications. Controlled experiments are carried out and the results show that the capability of GPS in tracking structural dynamics and complex signals can be improved with any of the filters. The performances of Vondrak and wavelet filters are almost the same and superior to the adaptive FIR and Kalman filters. Recommendations are given for the selection of filters and filter parameters for different situations based on an analysis of the advantages and disadvantages of each of the filters.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.37-46
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• 2015

The wireless electrocardiographic monitoring system(WDMS) is designed to be long term monitoring for the early detection of cardiac disorders. The current version of the WDMS can identify two types of cardiac rhythms in real-time, such as atrial fibrillation(AF) and normal sinus rhythm(NSR), which are very important to track cardiac-rhythm disorders. In this study, we proposed the analysis method to discriminate the characteristics statistically evaluated in both time and frequency domains between AF and NSR using various parameters in the heart rate variability(HRV). And we applied various ECG detection methods (e.g., difference operation method) and compared the results with those of the discrete wavelet transform(DWT) method. From the statistically results, we found that the parameters such as STD RR, STD HR, RMSSD, NN50, pNN50, RR Trian, and TNN(p<0.05) are significantly different between the AF and NSR patients in time domain. On the other hand, the frequency domain analysis results showed a significant difference in VLF power($ms^2$), LF power($ms^2$), HF power($ms^2$), VLF(%), LF(%), and HF(%). In particular, the parameters such as STD RR, RMSSD, NN50, pNN50, VLF power, LF power and HF power were considered as the most useful parameters in both AF and NSR patient groups. Our proposed method can be efficiently applied to early detection of abnormal conditions and prevent the such abnormals from becoming serious.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.55.4-56
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• 2015

The Hilbert-Huang Transform (HHT) is composed of the Empirical Mode Decomposition (EMD) and the Hilbert Spectral Analysis (HSA). The EMD decomposes any time series data into a small number of components called the Intrinsic Mode Functions (IMFs), compared to the Discrete Fourier Transform which decomposes a data into a large number of harmonic functions. Each IMF has varying amplitude and frequency with respect to time, which can be obtained by HSA. The time resolution of the modes in HHT is the same as that of the given time series, while in the Wavelet Transform, Constant Q Transform and Short-Time Fourier Transform, there is a tradeoff between the resolutions in frequency and time. Based on the time-dependent amplitudes of IMFs, we develop an Event Trigger Generator and demonstrate its efficiency by applying it to gravitational-wave data.