• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.126-129
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel type s as states of molecules in a lattice-like physical system defined on a GRF. Because of the MRFGRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular mteractions. The proposed adaptive iterative method was evaluated using simulation data generated by the Monte Carlo method. In the extensive experiments of this study, the proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.101-105
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• 1992

Machined graphite/epoxy composite surfaces were studied by using SEM(Scanning Electron Microscopy). surface profilometry and its analysis to determine suitable surface describing parameters for machined unidirectional and laminate composite surface. The surface roughness and profile are found to be highly dependent on the fiber layup direction and the measurement direction. Machined unidirectional and 0.deg. 45 .deg. 90 .deg. plies in laminate composite surface profiles are found to be Gaussian in the direction of machining. Since there exist bare fibers without matrix smearing in 0 .deg. ply, higher surface roughness values were found in this orientation. It was possible to machine 90 .deg. and -45 .deg. plies due to the adjacent plies, which were holding those plies. It was found that the microgeometrical variations in terms of roughness parameters Ra without Dy (maximum Damage Depth) region and Dy are better descriptors of the machined laminate composite surface than commonly used roughness parameters Ra and Ra. The characteristics of surface profiles in laminate composite are well represented in CHD (Cumulative Height Distribution) plot and PPD (Percentage Probability Density) plot. Also, the power spectral density function is shown to be capable of identifying the wavelength distribution of the machining damage.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.5 no.3
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• pp.36-47
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• 1994

The error performance of BPSK and QPSK signals with diversity reception in mobile-satellite channel is investigated considering nonlinearity of TWT (Traveling Wave Tube) amplifier in the presence of AWGN(Additive White Gaussian Noise) on the uplink and downlink paths. It is assumed that the fading on the dounlink path forms a Rician distribution. The Rician distribution is approximated by discrete probability values. The values are firstly found by Classical Moment Technique.

• Wind and Structures
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• v.2 no.2
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• pp.127-131
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• 1999

This paper describes probabilistic characteristics of damping in a tall building based on the results of full-scale measurement. It is found, through statistical analysis of the damping data, that the probability density function(PDF) of damping at the high amplitude plateau can be well represented by Normal distribution (Gaussian distribution). A stochastic damping model is proposed to estimate amplitude-dependent damping for practical application.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.457-462
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• 2005

An empirical way of a covariance matrix which expresses the odometry uncertainty of mobile robots is proposed. This method utilizes PC-method which removes systematic errors of odometry. Once the systematic errors are removed, the odometry error can be modeled using the Gaussian probability distribution, and the parameters of the distribution can be represented by the covariance matrix. Experimental results show that the method yields $5{\%}$ and $2.3{\%}$ offset for the synchro and differential drive robots.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.34-34
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• 2014

We investigate the constraints on the matter density ${\Omega}m$ and the cosmological constant ${\Omega}{\Lambda}$ using the gravitational lensed QSO (Quasi Stellar Object) systems from the Sloan Digital Sky Survey (SDSS) by analyzing the distribution of image separation. The main sample consists of 16 QSO lens systems with measured source and lens redshifts. We use a lensing probability that is simply defined by the gaussian distribution. We perform the curvature test and the constraints on the cosmological parameters as the statistical tests. The statistical tests have considered well-defined selection effects and adopt parameter of velocity dispersion function. We also applied the same analysis to Monte-Carlo generated mock gravitational lens samples to assess the accuracy and limit of our approach. As the results of these statistical tests, we find that only the excessively positively curved universe (${\Omega}m+{\Omega}{\Lambda}$ > 1) are rejected at 95% confidence level. However, if the informations of the galaxy as play a lens are measured accurately, we confirm that the gravitational lensing statistics would be the most powerful tool.

• Journal of KIISE:Information Networking
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• v.29 no.5
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• pp.553-561
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• 2002

We present a novel service discipline, called linear service discipline, to serve multiple QoS queues sharing a resource and analyze its properties. The linear server makes the output traffic and the queueing dynamics of individual queues as a linear function of its input traffic. In particular, if input traffic is Gaussian, the distributions of queue length and output traffic are also Gaussian with their mean and variance being a function of input mean and input power spectrum (equivalently, autocorrelation function of input). Important QoS measures including buffer overflow probability and queueing delay distribution are also expressed as a function of input mean and input power spectrum. This study explores a new direction for network-wide traffic management based on linear system theories by letting us view the queueing process at each node as a linear filter.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.635-644
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• 1994

This study investigated mainly on the flow characteristics of a droplet in the cross region of twin spray. The velocities of the droplet were measured along the axial and radial direction, and the flow characteristics of the droplet were statistically analyzed. For the statistical analysis, the probability density of the turbulent components has been studied, and then the Reynolds shear stress, the skewness and the flatness factors were calculated, and compared with the Gaussian value. Two pressure swirl stomizers were used for the twin spray system and kerosene was employed as the working liquid. 2-D PDA(particle dynamic analyzer) was used for the purpose of the measurement of droplet size and velocities. As a result, it was found that (1) the droplets collision was taken place strongly in the cross region. So, a large momentum loss of droplets due to the loss of natural movement direction was occurred, and momentum loss of radial direction was greater than that of axial direction. (2) The axial direction skewness factor approached to zero like the Gaussian distribution in the cross region of twin spray. (3) In the cross region of twin spray, the fluctuation instability of droplet was increased because of the development of the turbulence characteristics due to the droplet collision.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2299-2318
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• 2019

Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.163-168
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• 2009

Most image segmentation methods are to represent observed feature vectors at each pixel, which are assumed as appropriated probability models. These models can be used by statistical estimating or likelihood clustering algorithms of feature vectors. EM algorithms have some calculation problems of maximum likelihood for unknown parameters from incomplete data and maximum value in post probability distribution. First, the performance is dependent upon starting positions and likelihood functions are converged on local maximum values. To solve these problems, we mixed the Gausian function and histogram at all the level values at the image, which are proposed most suitable image segmentation methods. This proposed algoritms are confirmed to classify most edges clearly and variously, which are implemented to MFC programs.