• Geophysics and Geophysical Exploration
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• v.8 no.2
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• pp.170-176
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• 2005

Recently the velocity stack inversion is having many attentions as an useful way to perform various seismic data processing. In order to be used in various seismic data processing, the inversion method used should have properties such as robustness to noise and parsimony of the velocity stack result. The IRLS (Iteratively Reweighted Least-Squares) method that minimizes ${L_1}-norm$ is the one used mostly. This paper introduce another method, CGG (Conjugate Guided Gradient) method, which can be used to achieve the same goal as the IRLS method does. The CGG method is a modified CG (Conjugate Gradient) method that minimizes ${L_1}-norm$. This paper explains the CGG method and compares the result of it with the one of IRSL methods. Testing on synthetic and real data demonstrates that CGG method can be used as an inversion method f3r minimizing various residual/model norms like IRLS methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1591-1598
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• 2008

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. In this paper, we propose Z. Cao's fuzzy inference method with learning ability which is used a gradient descent method in order to improve the performances. It is hard to determine the relation matrix elements by trial and error method. Because this method is needed many hours and effort. Simulation results are applied nonlinear systems show that the proposed inference method using a gradient descent method has good performances.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.126-135
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• 2014

The Euclidean distance between error probability density functions (EDEP) has been used as a performance criterion for supervised adaptive signal processing in impulsive noise environments. One of the drawbacks of the EDEP algorithm is a heavy computational complexity due to the double summation operations at each iteration time. In this paper, a recursive method to reduce its computational burden in the estimation of the EDEP and its gradient is proposed. For the data block size N, the computational complexity for the estimation of the EDEP and its gradient can be reduced to O(N) by the proposed method, while the conventional estimation method has $O(N^2)$. In the performance test, the proposed EDEP and its gradient estimation yield the same estimation results in the steady state as the conventional block-processing method. The simulation results indicates that the proposed method can be effective in practical adaptive signal processing.

• The Journal of the Acoustical Society of Korea
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• v.32 no.3
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• pp.279-285
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• 2013

In this paper, we propose a novel speech enhancement method to improve the performance of the conventional global soft decision which is based on the spectral gradient method applied to the ratio of a priori speech absence and presence probability value (q). Conventional global soft decision scheme used a fixed value of q in accordance with the hypothesis assumed, but the proposed algorithm is a technique for improving the speech absence probability which is applied adaptively variable value of q according to the speech presence or absence in the previous two frames and the conditions of the spectral gradient value. Experimental results show that the proposed improved global soft decision method based on the spectral gradient method yields better results compared to the conventional global soft decision technique based on the performance criteria of the ITU-T P. 862 PESQ (Perceptual Evaluation of Speech Quality).

• Korean Journal of Materials Research
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• v.33 no.2
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• pp.54-62
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• 2023

The most comprehensive and particularly reliable method for non-destructively measuring the residual stress of the surface layer of metals is the sin²ψ method. When X-rays were used the relationship of ε_φψ-sin²ψ measured on the surface layer of the processing metal did not show linearity when the sin²ψ method was used. In this case, since the effective penetration depth changes according to the changing direction of the incident X-ray, σ_φ becomes a sin²ψ function. Since σ_φ cannot be used as a constant, the relationship in ε_φψ-sin²ψ cannot be linear. Therefore, in this paper, the orthogonal function method according to Warren's diffraction theory and the basic profile of normal distribution were synthesized, and the X-ray diffraction profile was calculated and reviewed when there was a linear strain (stress) gradient on the surface. When there is a strain gradient, the X-ray diffraction profile becomes asymmetric, and as a result, the peak position, the position of half-maximum, and the centroid position show different values. The difference between the peak position and the centroid position appeared more clearly as the strain (stress) gradient became larger, and the basic profile width was smaller. The weighted average strain enables stress analysis when there is a strain (stress) gradient, based on the strain value corresponding to the centroid position of the diffracted X-rays. At the 1/5 I_max max height of X-ray diffraction, the position where the diffracted X-ray is divided into two by drawing a straight line parallel to the background, corresponds approximately to the centroid position.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1987.04a
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• pp.184-187
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• 1987

The method of Conjugate Gradient(C.G.M) is applied to the solution of current distribution from body of revolution (B.O.R).Using the C.G.M it is possible to analyze electrically large arbtrarily oriented B.O.R. The fundamental differences between C.G.M and moment method are outlined. This method converges for any initial guess and this techniqe gurantees a monotonic convergence. Numerical results are presented for electromagnetic case which show good agreement with moment solution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.6-22
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• 1991

This thesis presents a parallel implementation of an iterative method for large scale, sparse linear system and gives result of computational experiments performed on both single transputer and multi transputer parallel computers. To solve linear system, we use conjugate gradient method and develope data storage techinique, data communication scheme. In addition to the explanation of conjugate gradient method, the result of computational experiment is summarized.

• Korean Journal of Mathematics
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• v.7 no.2
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• pp.245-269
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• 1999

Multigrid method and acceleration by conjugate gradient method for first-order system least squares (FOSLS) using bilinear finite elements are developed for various boundary value problems of planar linear elasticity. They are two-stage algorithms that first solve for the displacement flux variable, then for the displacement itself. This paper focuses on solving for the displacement flux variable only. Numerical results show that the convergence is uniform even as the material becomes nearly incompressible. Computations for convergence factors and discretization errors are included. Heuristic arguments to improve the convergences are discussed as well.

• Communications of the Korean Mathematical Society
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• v.16 no.3
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• pp.509-518
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• 2001

The purpose of this paper is to propose a numerical algorithm for the problem of coefficient identification of the scalar wave equation based on a local observation on the boundary: Determine the unknown coefficient function with the knowledge of simultaneous Dirichlet and Neumann boundary values on a part of boundary. To find the unknown coefficient function, the unknown Neumann boundary value is also identified. We recast our inverse problem to variational problem. The gradient method is applied to find the minimizing functions. We confirm the effectiveness of our algorithm by numerical experiments.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.901-911
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• 2009

In this paper, we propose a construction technique of two-level composite gradient map to automatically track a face with large movement in successive frames. Our method is composed of three main steps. First, the gradient maps with two-level resolution are generated for fast convergence of active contour. Second, to recognize the variations of face between successive frames and remove the neighbor background, weighted composite gradient map is generated by combining the composite gradient map and difference mask of previous and current frames. Third, to prevent active contour from converging local minima, the energy slope is generated by using closing operation. In addition, the fast closing operation is proposed to accelerate the processing time of closing operation. For performance evaluation, we compare our method with previous active contour model-based face tracking methods using a visual inspection, robustness test and processing time. Experimental results show that our method can effectively track the face with large movement and robustly converge to the optimal position even in frames with complicated background.