• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.989-995
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• 2022

Currently, the demand for image processing is increasing due to the development of IT technology, and active research is being conducted. Since image data generates image noise due to various external causes, and thus degrades the performance of the image, noise removal is essential. Salt and Pepper noise is a representative image noise, and various studies are being conducted to remove it. Existing algorithms include A-TMF, AFMF, LIWF, but these have the disadvantage that their performance is somewhat insufficient. Therefore, in this paper, we propose an algorithm that performs filtering using linear interpolation with effective pixels existing around the central pixel only in case of noise after performing noise judgment in order to efficiently remove salt and pepper noise. In order to judge the performance of the proposed algorithm, it was compared using the processed image of the previously studied algorithm and PSNR.

• Journal of Aerospace System Engineering
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• v.7 no.1
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• pp.8-18
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• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1297-1301
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• 2007

The Conventional noise control attempts to simply reduce the level of product noise. But it is very straight forward way that we have consider human perception on noise. Since human listening is very sensitive to sound. Evaluation of the sound quality of a Vacuum Cleaner is studied base on human sensibility engineering. In this paper, we choose two Vacuum Cleaners that are sold in Korea and reduced noise control. Comparison Method is used to evaluate noise and preference of Vacuum Cleaner by steps. The sound quality of Vacuum Cleaner noise is analyzed by employing the subjective evaluation and by representing them in terms of the objective quantities. Semantic Differential Method is used to study sound quality Evaluation. To analyze the sound quality of Vacuum Cleaner noise, consider the coefficients of correlation between sound metrics and subjective rating. The linear regression models were obtained for the subjective evaluation and sound quality metrics.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1494-1498
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• 2007

Impulsive shooting noise is basically complex phenomenon which contains the linear and non-linear characteristics. For those reasons, numerical analysis of impulsive shooting noise has the difficulties in control of the numerical stability and accuracy on the simulation. In this research, Wave-number Extended Finite Volume Scheme (WEFVS) is applied to the numerical analysis of impulsive shooting noise. In the muzzle blast flow simulation, the generation of the precursor wave and the induced vortex ring are observed. Consequently, blast wave. vortex ring interaction and vortex ring. bow shock wave interaction are evaluated on the shooting process using the accurate and stable scheme. The sound generation in the interactions can be explained by the vorticity transport theorem. The shear layer is evolved behind the projectiles due to the jet flow. In these computations, the impulsive shooting noise is generated by the complex interaction with shooting process and is propagated to the far-field boundary. The impulsive shooting noise generation can be observed by the applications of WEFVS and analyzed by the physical phenomena.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.12
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• pp.1223-1228
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• 2010

The conventional noise control attempts to simply reduce the level of product noise. But it is very straight forward way that we have considered human perception on noise. Since human listening is very sensitive to sound. Evaluation of the sound quality of a vacuum cleaner is studied base on human sensibility engineering. In this paper, we choose six vacuum cleaners that are sold in Korea and reduced noise control. The sound quality of vacuum cleaner noise is analyzed by employing the subjective evaluation and by representing them in terms of the objective quantities. Semantic differential method is used to study sound quality Evaluation. To analyze the sound quality of vacuum cleaner noise, consider the coefficients of correlation between sound metrics and subjective rating. The linear regression models were obtained for the subjective evaluation and sound quality metrics.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.47-56
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• 2004

• Journal of Astronomy and Space Sciences
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• v.28 no.4
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• pp.267-271
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• 2011

I developed an enhanced correction method for Ricean bias which occurs in linear polarization measurement. Two known methods for Ricean bias correction are reviewed. In low signal-to-noise area, the method based on the mode of the equation gives better representation of the fractional polarization. But a caution should be given that the accurate estimation of noise level, i.e. ${\sigma}$ of the polarized flux, is important. The maximum likelihood method is better choice for high signal-to-noise area. I suggest a hybrid method which uses the mode of the equation at the low signal-to-noise area and takes the maximum likelihood method at the high signal-to-noise area. A modified correction coefficient for the mode solution is proposed. The impact on the depolarization measure analysis is discussed.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.640-644
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• 2010

When we talk with hands-free in a car or noisy lobby, the performance of the echo canceller degrade because background noise added to echo caused by the distance from mouth to microphone is relatively long. It gives a reason for necessity of noise-robust and high convergence speed adaptive algorithm. And if acoustic echo canceller operated not perfectly, residual signal going through the echo canceller to far-end speaker remains residual echo, which degrade quality of talk. To solve this problem, post-processing needed to remove residual echo ones more. In this paper, we propose a new acoustic echo canceller, which has noise robust and high convergence speed, linked with linear predictor as a post-processor. By computer simulation, it is confirmed that the proposed algorithm shows better performance from acoustic interference cancellation (AIC) viewpoint.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.383-391
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• 2009

In this paper, blind equalization using a modified Fuzzy C-Means algorithm with Gaussian Weights (MFCM_GW) is attempted to the heavy noise-corrupted channels. The proposed algorithm can deal with both of linear and nonlinear channels, because it searches for the optimal channel output states of a channel instead of estimating the channel parameters in a direct manner. In contrast to the common Euclidean distance in Fuzzy C-Means (FCM), the use of the Bayesian likelihood fitness function and the Gaussian weighted partition matrix is exploited in its search procedure. The selected channel states by MFCM_GW are always close to the optimal set of a channel even the additive white Gaussian noise (AWGN) is heavily corrupted in it. Simulation studies demonstrate that the performance of the proposed method is relatively superior to existing genetic algorithm (GA) and conventional FCM based methods in terms of accuracy and speed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.7
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• pp.729-739
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• 1990

This paper deals with the fault detection problem in uncertain linear/non-linear systems having both undermodelling and noise. A robust fault detection method is presented which accounts for the effects of noise, model mismatch and nonlinearities. The basic idea is to embed the unmodelled dynamics in a stochastic process and to use the nominal model with a predetermined fixed denominator. This allows the input /output relationship to be represented as a linear function of the system parameters and also facilitate the quatification of the effect of noise, model mismatch and linearization errors on parameter estimation by the Bayesian method. Comparisons are made via simulations with traditional fault detection methods which do not account for model mismatch or linearization errors. The new method suggested in this paper is shown to have a marked improvement over traditional methods on a number of simulations, which is a consequence of the fact that the new method explicitly for the effects of undermodelling and linearization errors.