• Structural Engineering and Mechanics
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• v.6 no.5
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• pp.473-484
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• 1998

The first and second moments of response variables for SDOF systems with hysteretic nonlinearity are obtained by a direct linearization procedure. This adaptation in the implementation of well-known statistical linearization methods, provides concise, model-independent linearization coefficients that are well-suited for numerical solution. The method may be applied to systems which incorporate any hysteresis model governed by a differential constitutive equation, and may be used for zero or non-zero mean random vibration. The implementation eliminates the effort of analytically deriving specific linearization coefficients for new hysteresis models. In doing so, the procedure of stochastic analysis is made independent from the task of physical modeling of hysteretic systems. In this study, systems with three different hysteresis models are analyzed under various zero and non-zero mean Gaussian White noise inputs. Results are shown to be in agreement with previous linearization studies and Monte Carlo Simulation.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.231-241
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• 2013

In this paper, we propose an average approximation filter which can effectively remove the noises of the images. The noises include impulse noises, gaussian noises and mixed noises. The algorithm is as follows. First, as a step of noise detection, we find whether the difference between the pixel value and the average value is greater than the threshold value or not after getting the average value that removed the minimum and maximum values in the applied mask. If the pixel value is greater than the threshold value, the pixel value is processed as noise. If it is less than or equal to the threshold value, it is processed as non-noise. Next, as the noise reduction step, we output the approximate value in mask as the pixel value and the average value except the minimum and maximum values of the pixel including the noise. As the result of applying this average approximation filter to the mixed noise images, the approximation filter can reduce the noises effectively more than 0.4[dB] as compared with applying the median filter and the average filter, respectively.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.5 no.4
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• pp.3-17
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• 1994

The error probability of QPSK and DPSK signals with diversity reception technique in m-distribution fading plus impulsive noise environments has been derived and the error probability is evaluated and compared with that in Gaussian noise environment. The error performance degrades as impulsive noise becomes strong and degree of degradation of signal performance in QDPSK signal is larger than that in QPSK signal. The diversity reception technique can improve the error performance not only in fading plus Gaussian noise environment but in fading plus impulsive noise environment. When diversity reception technique is used, the improvement of error performance attains about 10dB to 15dB in terms of CNR as compared with that in non diversity reception. Among diversity techniques the maximal ratio combining is must effective. When diversity reception and coding techniques are used together in impulsive noise plus Rayleigh fading environments, the improvement of error performance attains about 12dB to 15dB in terms of CNR as compared with that of only diversity reception technique case and the improvement of error perform- ance in RS coding attains about 2dB in terms of CNR as compared with that of BCH coding case.

• Journal of Internet Computing and Services
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• v.14 no.1
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• pp.9-14
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• 2013

The criterion of zero-error probability provides a limitation on error probability functions being used for adaptive systems when the error samples are shifted by the influence of DC-bias noise. In this paper, we employ a bias term in the error distribution and propose a new criterion of the biased zero-error probability with error being zero. Also, by maximizing the proposed criterion on expanded filter structures, a supervised adaptive algorithm has been derived. From the simulation results of supervised equalization, the algorithm based on the proposed criterion yielded zero-centered and highly concentrated error samples without disturbance in the environments of strong impulsive and DC-bias noise.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.386-393
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• 2010

A defect in an image is a set of pixels forming an irregular shape. Since a defect, in most cases, is not easy to be modeled mathematically, the defect detection problem still resides in a research area. If a given image, however, composed by certain patterns, a defect can be detected by the fact that a non-defect area should be explained by another patch in terms of a rotation, translation, and noise. In this paper, therefore, the defect detection method for a repeated multi-patterned image is proposed. The proposed defect detection method is composed of three steps. First step is the interest point detection step, second step is the selection step of a appropriate patch size, and the last step is the decision step. The proposed method is illustrated using SEM images of semiconductor wafer samples.

• Journal of The Korean Astronomical Society
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• v.47 no.6
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• pp.255-258
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• 2014

Using sunspot number data from 270 historical stations for the period 1981-2013, we investigate their personal reduction coefficients (k) statistically. Chang & Oh (2012) perform a simulation showing that the k varies with the solar cycle. We try to verify their results using observational data. For this, a weighted mean and weighted standard deviation of monthly sunspot number are used to estimate the error from observed data. We find that the observed error (noise) is much smaller than that used in the simulation. Thus no distinct k-variation with the solar cycle is observed contrary to the simulation. In addition, the probability distribution of k is determined to be non-Gaussian with a fat-tail on the right side. This result implies that the relative sunspot number after 1981 might be overestimated since the mean value of k is less than that of the Gaussian distribution.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.18-26
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• 2008

The invariance relation existing in the non-negative matrix factorization (NMF) is used for constructing robust image hashes in this work. The image is first re-scaled to a fixed size. Low-pass filtering is performed on the luminance component of the re-sized image to produce a normalized matrix. Entries in the normalized matrix are pseudo-randomly re-arranged under the control of a secret key to generate a secondary image. Non-negative matrix factorization is then performed on the secondary image. As the relation between most pairs of adjacent entries in the NMF's coefficient matrix is basically invariant to ordinary image processing, a coarse quantization scheme is devised to compress the extracted features contained in the coefficient matrix. The obtained binary elements are used to form the image hash after being scrambled based on another key. Similarity between hashes is measured by the Hamming distance. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as Gaussian filtering, moderate noise contamination, JPEG compression, re-scaling, and watermark embedding. Hashes of different images have very low collision probability. Tampering to local image areas can be detected by comparing the Hamming distance with a predetermined threshold, indicating the usefulness of the technique in digital forensics.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.321-326
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• 2019

Image denoising methods based on block matching are founded on the experimental observations that neighboring patches or blocks in images retain similar features with each other, and have been proved to show superior performance in denoising different kinds of noise. The methods, however, take into account only neighboring blocks in searching for similar blocks, and ignore the characteristic features of the reference block itself. Consequently, denoising performance is negatively affected when outliers of the Gaussian distribution are included in the reference block which is to be denoised. In this paper, we propose an expanded block matching method in which noisy images are first decomposed into a number of bit-planes, then the range of true signals are estimated based on the distribution of pixels on the bit-planes, and finally outliers are replaced by the neighboring pixels belonging to the estimated range. In this way, the advantages of the conventional Gaussian filter can be added to the blocking matching method. We tested the proposed method through extensive experiments with well known test-bed images, and observed that performance gain can be achieved by the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.851-858
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• 2016

This paper presents a new statistical voice activity detection (VAD) based on the probabilistic interpretation of nonnegative matrix factorization (NMF). The objective function of the NMF using Kullback-Leibler divergence coincides with the negative log likelihood function of the data if the distribution of the data given the basis and encoding matrices is modeled as Poisson distributions. Based on this probabilistic NMF, the VAD is constructed using the likelihood ratio test assuming that speech and noise follow Poisson distributions. Experimental results show that the proposed approach outperformed the conventional Gaussian model-based and NMF-based methods at 0-15 dB signal-to-noise ratio simulation conditions.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.87-93
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• 2001

As a new type of a linear decorrelating receiver, the Pseudo-Decorrelator was presented for asynchronous code division multiple access systems by the author. In this paper, the concept of the Pseudo-Decorrelator is extended to derive a receiver for WCDMA uplink systems over an additive white Gaussian noise channel. Starting with the analysis of the multiple access components of the decision statistics, a non-square cross-correlation matrix for each bit is obtained. This cross-correlation matrix is then inverted, and the inverted matrix is applied to the decision statistics obtained from a conventional receiver. In this receiver, the detection process can be started after the first three consecutive bits are received. Simulation results are presented for K-user systems over an additive white Gaussian noise channel under the circumstances in which synchronization errors, including time delay errors and carrier phase errors exist. It is shown that the proposed receiver performs better than a conventional receiver and parallel interference canceller.