• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.47-54
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• 2005

In general, wavelet coefficients are composed of a few large coefficients and a lot of small coefficients. In this paper, we propose image denoising algorithm using Bernoulli-Gaussian mixture model based on sparse characteristic of wavelet coefficient. The Bernoulli-Gaussian mixture is composed of the multiplication of Bernoulli random variable and Gaussian mixture random variable. The image denoising is performed by using Bayesian estimation. We present an effective denoising method through simplified parameter estimation for Bernoulli random variable using local expected squared error. Simulation results show our method outperforms the states-of-art denoising methods when using orthogonal wavelets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.3
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• pp.263-279
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• 1989

In part-1 of this paper, the error rate equations of digitally modulated signals transmitted though the Gaussian/Impulsive noise channel have been derived. Using the derived equations for the error probabilities of ASK, QAM, CPSK, DPSK, FSK and MSK signals, the error rate performances of digital modulation systems have been evaluated and represented in the figures as the functions of carrier-to-noise power ratio(CNR), impulsive index, and the ration of Gaussian noise power component to impulsive noise power component. The results are shown in graphs to known how much impulsive noise effects on digital signals than Gaussian noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.3
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• pp.280-292
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• 1989

In this paper, the error rate equations of digitally modulated signals transmitted through the channel which is not only Gaussian/Impulsive noise but also multi-path fading have been derived. Using the derived equations for the error probabilities of ASK, QAM, CPSK, DPSK, FSK, and MSK signals, the error rate performances of digital modulation systems have been evaluated and represented in the graphs as the functions of CNR, Impulsive indes, the ratio of Gaussian noise power component to Impulsive noise power component, and fading figures. The results show that, in the deep fading environment, the error is occurred more frequency by Gaussian noise than Impulsive noise. And the comparison of various systems certifies that PSK is superior to the ohter systems in the deep fading or shallow fading environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.461-470
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• 1996

In this paper, the average probability of bit error of direct sequence spread spectrum multiple access (DS/SSMA) communication system is derived over frequency-selective rician fading channels with Gaussian and impulsive noise. Multiple access interference due to K asynchronous users transmitting simultaneously is computed using the characteristic function method, and compared with Gaussian approximation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.6
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• pp.67-79
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• 1982

The stability of general pulse-width modulation system with Gaussian random disturbance was discussed . General system is divided into nonlinear and linear elements using the conventional describing function method. The concept of the equivalent admittance was used to find the transfer characteristic of the nonlinear element of the system. In this paper the self-sustained oscillation condition in the autonomous system was derived and the results was analyzed with computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.3
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• pp.204-215
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• 1987

In this paper, 16QAM techniques are described. The evaluated error rate performences are shown in figures as parameters of carrier-to-noise power ratio(CNR), carrier-to-interference power ratio(CIR), impulsive noise index, and Gaussian to impulsive noise power ration. Also, the error rate performances are measured experimentally by hardware system and compared with the theoretical results.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.15-22
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• 2011

Principal component analysis (PCA) is a well-known method for dimensionality reduction and feature extraction while maintaining most of the variation in data. Although PCA has been applied in many areas successfully, it is sensitive to outliers and only valid for Gaussian distributions. Several variants of PCA have been proposed to resolve noise sensitivity and, among the variants, improved robust fuzzy PCA (RF-PCA2) demonstrated promising results. RF-PCA, however, is still a linear algorithm that cannot accommodate non-Gaussian distributions. In this paper, a non-linear algorithm that combines RF-PCA2 and kernel PCA (K-PCA), called improved robust kernel fuzzy PCA (RKF-PCA2), is introduced. The kernel methods make it to accommodate non-Gaussian distributions. RKF-PCA2 inherits noise robustness from RF-PCA2 and non-linearity from K-PCA. RKF-PCA2 outperforms previous methods in handling non-Gaussian distributions in a noise robust way. Experimental results also support this.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1990.06a
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• pp.762-766
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• 1990

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.52-61
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• 2006

Orthogonal wavelet tansform which is generally used in image and signal processing applications has limited performance because of lack of shift invariance and low directional selectivity. To overcome these demerits complex wavelet transform has been proposed. In this paper, we present an efficient image denoising method using dual-tree complex wavelet transform and Bernoulli-Gauss prior model. In estimating hyper-parameters for Bernoulli-Gaussian model, we present two simple and non-iterative methods. We use hypothesis-testing technique in order to estimate the mixing parameter, Bernoulli random variable. Based on the estimated mixing parameter, variance for clean signal is obtained by using maximum generalized marginal likelihood (MGML) estimator. We simulate our denoising method using dual-tree complex wavelet and compare our algorithm to well blown denoising schemes. Experimental results show that the proposed method can generate good denoising results for high frequency image with low computational cost.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.1
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• pp.1-14
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• 1996

The purpose of this paper is to analyze the performance of M-ary PSK communication system according to the types of electromagnetic interference in an impulsive noise environment. We have introduced Gaussian, sinusoidal and rectangular waves as a electromagnetic interference. Using the derived equations, we evaluated the error performance of the BPSK and QPSK system in the presence of electromagnetic interference and impulsive noise. From results, we have obtained that the Gaussian wave produced the most significant performance degradation and that sinusoidal wave produced more performance degradation than rectangular wave. Therefore, without knowing the types of electromagnetic interference, it is best to regard it as Gaussian wave when designing a communication system. In addition, we could found out that the error performance degrades as impulsive noise becomes strong and the error performance can not be improved significantly even the electromagnetic interference becomes weak. Therefore, this describes that the impulsive noise affects dominantly to the performance degradation.