• Smart Structures and Systems
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• v.10 no.4_5
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• pp.427-442
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• 2012

An effective approach for updating finite element model is presented which can provide reliable estimates for structural updating parameters from identified operational modal data. On the basis of the dynamic perturbation method, an exact relationship between the perturbation of structural parameters such as stiffness change and the modal properties of the tested structure is developed. An iterative solution procedure is then provided to solve for the structural updating parameters that characterise the modifications of structural parameters at element level, giving optimised solutions in the least squares sense without requiring an optimisation method. A regularization algorithm based on the Tikhonov solution incorporating the generalised cross-validation method is employed to reduce the influence of measurement errors in vibration modal data and then to produce stable and reasonable solutions for the structural updating parameters. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is employed to demonstrate the effectiveness and applicability of the proposed model updating technique. The results from the benchmark problem studies show that the proposed technique can successfully adjust the reduced finite element model of the structure using only limited number of frequencies identified from the recorded ambient vibration measurements.

• Journal of the Korean Chemical Society
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• v.40 no.1
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• pp.20-27
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• 1996

A stable and accurate inverse method for extracting potential from spectroscopic data studied. The method is based on the Tikhonov regularization method to overcome the possible instability of nonlinear inverse problems using a priori smooth properties of the potential energy surface. The merit of this method is to treat the potential as continuous functions of the intermolecular coordinates instead of the conventional parameter fitting of restricted potential forms. Numerical study for the Ar-Ar show that from spectroscopic data the exact potential has been recovered whole region and the discrepancies by the dispersion force observed at the large distance between the exact and Morse potential or from RKR method can be eliminated by this method.

• Journal of Korean Society of Steel Construction
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• v.16 no.5 s.72
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• pp.543-553
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• 2004

This paper covered two related subjects: the use of the inverse modal perturbation technique to assess structural damage in existing structures; and the use of a seismic capacity evaluation to assess damaged structures, with the aid of the identified structural damage. The substructural identification and the Tikhonov regularization algorithm were incorporated for efficient damage assessment of complex and large frame structures. The seismic capacity of a damaged structure was evaluated by comparing the structure's seismic responses and seismic damage indices. The effectiveness of the proposed method has been investigated through the numerical simulation study for a twenty-story frame structure with undamaged and damaged cases, and also different earthquake excitations.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.561-571
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• 2012

The MTF(Modulation Transfer Function) is one of quality assesment factors to evaluate the performance of satellite images. Image restoration is needed for MTF compensation, but it is an ill-posed problem and doesn't have a certain solution. Lots of filters were suggested to solve this problem, such as Inverse Filter(IF), Pseudo Inverse Filter(PIF) and Wiener Filter(WF). The most commonly used filter is a WF, but it has a limitation on distinguishing signal and noise. The L-curve-based Modified Wiener Filter(MWF) is a solution technique using a Tikhonov regularization method. The L-curve is used for estimating an optimal regularization parameter. The image restoration was performed with Dubaisat-1 images for PIF, WF, and MWF. It is found that the image restored with MWF results in more improved MTF by 20.93% and 10.85% than PIF and WF, respectively.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.413-421
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• 2015

Regularized Blind Deconvolution is a problem applicable in degraded images in order to bring the original image out of blur. Multichannel blind Deconvolution considered as an optimization problem. Each step in the optimization is considered as variable splitting problem using an algorithm called Alternating Minimization Algorithm. Each Step in the Variable splitting undergoes Augmented Lagrangian method (ALM) / Bregman Iterative method. Regularization is used where an ill posed problem converted into a well posed problem. Two well known regularizers are Tikhonov class and Total Variation (TV) / L2 model. TV can be isotropic and anisotropic, where isotropic for L2 norm and anisotropic for L1 norm. Based on many probabilistic model and Fourier Transforms Image deblurring can be solved. Here in this paper to improve the performance, we have used an adaptive regularization filtering and isotropic TV model Lp norm. Image deblurring is applicable in the areas such as medical image sensing, astrophotography, traffic signal monitoring, remote sensors, case investigation and even images that are taken using a digital camera / mobile cameras.

• ETRI Journal
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• v.32 no.6
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• pp.901-910
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• 2010

As a supplement to X-ray mammography, microwave imaging is a new and promising technique for breast cancer detection. Through solving the nonlinear inverse scattering problem, microwave tomography (MT) creates images from measured signals using antennas. In this paper, we describe a developed MT system and an iterative Gauss-Newton algorithm. At each iteration, this algorithm determines the updated values by solving the set of normal equations using Tikhonov regularization. Some examples of successful image reconstruction are presented.

• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.365-369
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• 2009

Identification is considered to be among the main applications of inverse theory and its objective for a given physical system is to use data which is easily observable, to infer some of the geometric parameters which are not directly observable. In this paper, a parameter identification method using inverse problem methodology is proposed. The minimisation of the objective function with respect to the desired vector of design parameters is the most important procedure in solving the inverse problem. The conjugate gradient method is used to determine the unknown parameters, and Tikhonov's regularization method is then used to replace the original ill-posed problem with a well-posed problem. The simulation and experimental results are presented and compared.

• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.353-363
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• 2013

A variant of the global conjugate gradient method for solving general linear systems with multiple right-hand sides is proposed. This method is called as the global conjugate gradient linear least squares (Gl-CGLS) method since it is based on the conjugate gradient least squares method(CGLS). We present how this method can be implemented for the image deblurring problems with Neumann boundary conditions. Numerical experiments are tested on some blurred images for the purpose of comparing the computational efficiencies of Gl-CGLS with CGLS and Gl-LSQR. The results show that Gl-CGLS method is numerically more efficient than others for the ill-posed problems.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1089-1090
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• 2008

In this paper, it is applied the reconstruction algorithm to detection of breast cancer. To solve the forward and inverse problem, Finite-Difference Time-Domain (FDTD), Tikhonov regularization and Gauss-Newton method are used. And to confirm the accuracy of the algorithm, it is applied to arbitrary model.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.597-602
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• 2008

Most of structural analyses are concerned with the deformation and stress in a body subjected to external loads. In many fields, however, the interpretation of inverse problems is needed to determine surface tractions or internal stresses. In this study, the inverse processes by using the finite elements and the boundary elements are formulated for the evaluation of internal residual stresses from displacements measured on a remote surface. Small errors in the measured displacements often result in a substantial loss of accuracy of an inverse system. We use the Tikhonov regularization techniques to regularize the ill-conditioned system. Advantages and disadvantages are discussed through numerical examples.