• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.49-54
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• 2013

WPM(Wavelet Packet Modulation) is multicarrier system which is suitable for high speed transmission. The main advantage of using the WPM system is the fact that the flexible system effectively can be realized by the combination of filter coefficient. On the other hand, the major problem of multicarrier system is known to be the high PAPR. In this paper we propose WPM system that has a minimum PAPR by using filter coefficient adjustment method. We first derive the filter coefficient equation and then select the coefficient that has a minimum PAPR. we conduct WPM system by using a selected coefficient and we demonstrate the system performance by using computer simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.3 s.22
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• pp.73-82
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• 2005

This paper describes shock waveform synthesis methods for a shock response spectnlm over a short time interval with which intereference between parts within a test item is increased to perform a sufficient shock test for damage or malfunction which may be caused by the interference between parts, and a digital filter for obtaining a shock response history required for the shock waveform synthesis and a digital inverse filter for restoration by inversely using the digital filter. The time at which the maximax value occurs in the response history is detected in order to establish a delay time which is one of the parameters in the wavelet, on the condition that the natural frequency of SDOF system with a Q (quality factor) of 10 equals to the wavelet frequency of the zero delay wavelet input. A shock response spectrum over a short time interval and an abrupt change in the acceleration for an instant are illustrated as features of the synthesized waveform.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.1
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• pp.29-36
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• 2004

Generally, wavelet coefficients can be classified into two categories: large coefficients with much signal information and small coefficients with little signal component. This statistical characteristic of wavelet coefficient is approximated to Gaussian mixture model and efficiently applied to noise reduction. In this paper, we propose an image denoising method using mixture modeling of wavelet coefficients. Binary mask value is generated by proper threshold which classifies wavelet coefficients into two categories. Information of binary mask value is used to remove image noise. We also develope an enhancement method of mask value using morphological filter, and apply it to image denoising for improvement of the proposed method. Simulation results shows the proposed method have better PSNRs than those of the state of art denoising methods.

• Earthquakes and Structures
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• v.3 no.6
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• pp.839-852
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• 2012

Earthquake records are often analyzed in various earthquake engineering problems, making time-frequency analysis for such records of primary concern. The best tool for such analysis appears to be based on wavelet functions; selection of which is not an easy task and is commonly carried through trial and error process. Furthermore, often a particular wavelet is adopted for analysis of various earthquakes irrespective of record's prime characteristics, e.g. wave's magnitude. A wavelet constructed based on records' characteristics may yield a more accurate solution and more efficient solution procedure in time-frequency analysis. In this study, a low-pass reconstruction filter is obtained for each earthquake record based on multi-resolution decomposition technique; the filter is then assigned to be the normalized version of the last approximation component with respect to its magnitude. The scaling and wavelet functions are computed using two-scale relations. The calculated wavelets are highly efficient in decomposing the original records as compared to other commonly used wavelets such as Daubechies2 wavelet. The method is further advantageous since it enables one to decompose the original record in such a way that a clear time-frequency resolution is obtained.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.585-591
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• 2000

The wavelet transform is the most recent technique for processing signals with time-varying spectra. In this paper, the wavelet transform is utilized to improved the assessment and multi-resolution analysis of acoustic emission signals generating in partial discharge. This paper especially deals with the assessment of process statistical parameter using the features extracted from the wavelet coefficients of measured acoustic emission signals in case of applied voltage 20[kv]. Since the parameter assessment using all wavelet coefficients will often turn out leads to inefficient or inaccurate results, we selected that level-3 stage of multi decomposition in discrete wavelet transform. We applied FIR(Finite Impulse Response)digital filter algorithm in discrete to suppression for random noise. The white noise be included high frequency component denoised as decomposition of discrete wavelet transform level-3. We make use of the feature extraction parameter namely, maximum value of acoustic emission signal, average value, dispersion, skewness, kurtosis, etc. The effectiveness of this new method has been verified on ability a diagnosis transformer go through feature extraction in stage of acting(the early period, the last period) .

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1095-1100
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• 2003

The wavelet transform pair used simultaneously when two wavelets are designed to form an approximate Hilbert transform pair provide excellent property than present DWT(discrete wavelet transform), especially in field that detect wide-band signals like pulse and increase the bit rate at the same bandwidth. In this paper, the two dyadic wavelet bases which form an approximate Hilbert transform pair were designed, and flat delay filter which has the truncated coefficient vector is used in order that the two filters can form Hilbert transform relation in the process of design.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1215-1221
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• 1999

A high speed digital distance relaying algorithm based on a Wavelet Transformation is proposed. To obtain stable phasor values very quickly, first, a lowpass filter which has low cutoff frequency is used. Secondly, db2(Daubechies 2) Wavelet which has the data window of 4 samples is used. A FIR filter which removes the DC-offset component in current relaying signals is applied. In accordance with a series of tests, the operation time of the relaying algorithm is less than 3/4 cycles after faults in a 80 [km], 154[kV], 60[Hz] over-head transmission line system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1624-1632
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• 1996

Wavelet transform is widely used for high compression ratio image compression. It requeires a large memory when it is implemented by a hardware. Therefore, it is efficient to divide the entire image into blocks. Because the wavelet transform for divided blocks causes losses, pixels of the adjacent blocks are used. In the case of color image compression, the image is decomposed into brightness and color components, and then color components are downsampled. When the wavelet transform is performed by using pixels of adjacentblocks, the number of necessary pixels are doubled due to downsampling of color components. In this paper, we propose an efficient block wavelet transform using variablefilter length for brightness and color components. By using the proposed method, the number of pixels of adjacent blocks is optimized. We show the degradation of image quality due to the reduction of filter length for color components is negligible through simulations.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.595-607
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• 2010

This paper addresses the problem of reducing the speckle noise in SAR images by wavelet transformation, using a non-local means(NLM) filter originated for Gaussian noise removal. Log-transformed SAR image makes multiplicative speckle noise additive. Thus, non-local means filtering and wavelet thresholding are used to reduce the additive noise, followed by an exponential transformation. NLM filter is an image denoising method that replaces each pixel by a weighted average of all the similarly pixels in the image. But the NLM filter takes an acceptable amount of time to perform the process for all possible pairs of pixels. This paper, also proposes an alternative strategy that uses the t-test more efficiently to eliminate pixel pairs that are dissimilar. Extensive simulations showed that the proposed filter outperforms many existing filters terms of quantitative measures such as PSNR and DSSIM as well as qualitative judgments of image quality and the computational time required to restore images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.58-64
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• 2009

Digital radiography (DR) images are corrupted by the additive noise, and also distorted by system impulse response. These unwanted phenomena are obstacles to obtain the desired image. To recover the original image, we applied multiscale Wiener filters in wavelet domain for DR images. The multiscale Wiener filter is first proposed by Chen for the restoration of fractal signals which are distorted by the system impulse response and additive noise. In this paper, we extended the multiscale Wiener filter to the two dimensional data. To compare the performance of ours with others, some simulations are given for a couple of wavelet filters with different wavelet levels, system impulse reponses and various noise power. When the addive noise powers are between 20-32 dB, the signal to noise ratio(SNR) of the proposed system is 0.5-2.0 dB better than that of the traditional Wiener filter method.