• Geophysics and Geophysical Exploration
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• v.10 no.2
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• pp.138-146
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• 2007

This paper describes 2.5D induced polarization (IP) modeling and inversion algorithms using complex resistivity. The complex resistivity method has merits for acquiring more valuable information about hydraulic parameters and pore fluid than the conventional IP methods. The IP modeling and inversion algorithms are developed by allowing complex arithmetic in existing DC modeling and inversion algorithms. The IP modeling and inversion algorithms use a 2.5D DC finite-element algorithm and a damped least-squares method with smoothness constraints, respectively. The accuracy of the IP modeling algorithm is verified by comparing its responses of two synthetic models with two different approaches: linear filtering for a three-layer model and an integral equation method for a 3D model. Results from these methods are well matched to each other. The inversion algorithm is validated by a synthetic example which has two anomalous bodies, one is more conductive but non-polarizable than the background, and the other is polarizable but has the same resistivity as the background. From the inverted section, we can cleary identify each anomalous body with different locations. Furthermore, in order to verify its efficiency to the real filed example, we apply the inversion algorithm to another three-layer model which includes phase anomaly in the second layer.

• Journal of Drive and Control
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• v.13 no.4
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• pp.59-67
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• 2016

This paper proposes a model-prediction-based collision-avoidance algorithm for excavators for which the recursive-least-squares (RLS) estimation of the excavator's rotational inertia is used. To estimate the rotational inertia of the excavator, the RLS estimation with multiple forgetting and two updating rules for the nominal parameter and the forgetting factors was conducted based on the excavator-swing dynamics. The average value of the estimated rotational inertia that is for the minimizing effects of the estimation error was computed using the recursive-average method with forgetting. Based on the swing dynamics, the computed average of the rotational inertia, the damping coefficient for braking, and the excavator's braking angle were predicted, and the predicted braking angle was compared with the detected-object angle for a safety evaluation. The safety level defined in this study consists of the three levels safe, warning, and emergency braking. The analytical rotational-inertia-based performance evaluation of the designed estimation algorithm was conducted using a typical working scenario. The results of the safety evaluation show that the predictive safety-evaluation algorithm of the proposed model can evaluate the safety level of the excavator during its operation.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.107-113
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• 2009

In Digital On-Channel Repeaters (DOCR) of Terrestrial-DMB (Digital Multimedia Broadcasting), there exist feedback signals generated from transmit antenna and re-entering at receive antenna. Therefore DOCR becomes unstable unless the feedback signal is properly eliminated. Previous research proposed a feedback canceller to estimate the feedback channel to deal with this problem. However formerly used estimation algorithms show unsatisfied performance in terms of convergence rate and quality although their implementations are simple. This paper applies PNLMS (Proportionate Normalized Least Mean Squares) adaptive algorithm to feedback channel estimation and evaluates the performances which solve the problem of feedback signal effectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8C
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• pp.583-590
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• 2008

In this paper, we present a spatially adaptive post-processing algorithm for H.264 video coding standard to remove blocking artifacts. The loop filter of H.264 increases computational complexity of the encoder. Furthermore it doesn't clearly remove the blocking artifacts, resulting in over-blurring. For overcoming them, we combine the projection method with the Constraint Least Squares(CLS) method to restore the high quality image. To reflect the Human Visual System, we adopt the weight norm CLS method. Particularly pixel location-based local variance and laplacian operator are newly defined for the CLS method. In addition, the fact that correlation among adjoining pixels is high is utilized to constrain the solution space when the projection method is applied. Quantization Index(QP) of H.264 is also used to control the degree of smoothness. The simulation results show that the proposed post-processing filter works better than the loop filter of H.264 and converges more quickly than the CLS method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.331-337
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• 2018

This paper presents dynamic algorithm of the MLS(moving least squares) difference method using first order differential Approximation. The governing equations are only discretized by the first order MLS derivative approximation. The system equation consists of an assembly of the approximate function, so the shape of system equation is similar to FEM(finite element method). The CDM(central difference method) is used for time integration of dynamic equilibrium equation. The natural frequency analyses of the MLS difference method and FEM are performed, and two analysis results are compared. Also, the accuracy of the proposed numerical method is verified by displaying the dynamic analysis results together with the results by the existing second order differential approximation. In the process of assembling the first order MLS derivative approximation, the oscillation error was suppressed and the stress distribution was interpreted as relatively uniform.

• Structural Engineering and Mechanics
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• v.68 no.5
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• pp.563-573
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• 2018

Temperature-induced responses, such as strains and displacements, are related to the boundary conditions. Therefore, it is required to determine the boundary conditions to establish a reliable bridge model for temperature-induced responses analysis. Particularly, bridge bearings usually present nonlinear behavior with an increase in load, and the nonlinear boundary conditions cause significant effect on temperature-induced responses. In this paper, the bridge nonlinear boundary conditions were simulated as bilinear translational or rotational springs, and the boundary parameters of the bilinear springs were identified based on the measured temperature-induced responses. First of all, the temperature-induced responses of a simply support beam with nonlinear translational and rotational springs subjected to various temperature loads were analyzed. The simulated temperature-induced strains and displacements were assumed as measured data. To identify the nonlinear translational and rotational boundary parameters of the bridge, the objective function based on the temperature-induced responses is then created, and the nonlinear boundary parameters were further identified by using the nonlinear least squares optimization algorithm. Then, a beam structure with nonlinear translational and rotational springs was simulated as a numerical example, and the nonlinear boundary parameters were identified based on the proposed method. The numerical results show that the proposed method can effectively identify the parameters of the nonlinear boundary conditions. Finally, the boundary parameters of a real arch bridge were identified based on the measured strain data and the proposed method. Since the bearings of the real bridge do not perform nonlinear behavior, only the linear boundary parameters of the bridge model were identified. Based on the bridge model and the identified boundary conditions, the temperature-induced strains were recalculated to compare with the measured strain data. The recalculated temperature-induced strains are in a good agreement with the real measured data.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.407-416
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• 2021

An active phased array antennas can not only electrically steer the beam by controlling the weighting of the excitation signal, but can also form a pattern null in the direction of the interference source. The weight of the excitation signal to steer the main beam can be easily calculated based on the position of the radiating element. In addition, the weight of the excited signal for pattern null formation can also be calculated by setting the required radiation pattern and using WLSM(Weighted Least Squares Method). However, in a general wireless communication network environment, the location of the interference source is unknown. Therefore, an adaptive pattern null synthesis is needed. In this paper, it was confirmed that pattern null synthesis according to the required radiation characteristic was possible. And based on this, adaptive pattern null synthesis into the direction of an interference source was studied using a binary search algorithm based on observation area. As a result of conducting a simulation based on the presented technique, it was confirmed that adaptive pattern null forming into the direction of an interference is possible in efficient way.

• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.636-645
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• 2012

This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the consequent part of the fuzzy rules is developed by using four types of polynomials, namely constant, linear, quadratic, and modified quadratic. Information granulation realized with C-Means clustering helps determine the initial values of the apex parameters of the membership function of the fuzzy neural network. To enhance the flexibility of neural network, we use the WLS learning to estimate the coefficients of the polynomials. In comparison with ordinary least square commonly used in the design of fuzzy radial basis function neural networks, WLS could come with a different type of the local model in each rule when dealing with the FRBFNN. Since the performance of the FRBFNN model is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules and the orders of the polynomials present in the consequent parts of the rules, we carry out both structural as well as parametric optimization of the network. The proposed IMSSA that aims at the simultaneous minimization of complexity and the maximization of accuracy is exploited here to optimize the parameters of the model. Experimental results illustrate that the proposed neural network leads to better performance in comparison with some existing neurofuzzy models encountered in the literature.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.9
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• pp.952-958
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• 2014

In this paper, we propose a parametric sparse recovery algorithm(SRA) applied to a radar signal model, based on the compressive sensing(CS), for the ISAR(Inverse Synthetic Aperture Radar) image reconstruction from an incomplete radar-cross-section(RCS) data and for the estimation of rotation rate of a target. As the SRA, the iteratively-reweighted-least-square(IRLS) is combined with the radar signal model including chirp components with unknown chirp rate in the cross-range direction. In addition, the particle swarm optimization(PSO) technique is considered for searching correct parameters related to the rotation rate. Therefore, the parametric SRA based on the IRLS can reconstruct ISAR image and estimate the rotation rate of a target efficiently, although there exists missing data in observed RCS data samples. The performance of the proposed method in terms of image entropy is also compared with that of the traditional interpolation methods for the incomplete RCS data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.99-107
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• 2016

In order to maintain the precise positioning accuracy of the VLBI system, the shape deformation found in antenna structure should be monitored. In fact, reduced the antenna gaining of an electromagnetic wave reception from the Quasar has been particularly expected due to the shape deformation of main reflector in VLBI antenna. Therefore, the importance of shape deformation monitoring for the main reflector has been significantly increased. The main reflector has come out as the high potential for deformation in the VLBI structure. The fact has led us to investigate the monitoring system for the main reflector based on the efficient algorithm in accordance with the close-range photogrammetry, which of expecting to be utilized as the continuous and automated monitoring system for the structure deformation in the near future. Ten fitting lines were estimated with the TLS for feature points of distributed in all directions from the main reflector. The resultant intersection point of estimated fitting lines was calculated by using the nearest point calculation algorithm, based on those non-intersection lines. Following to the intuitive basis for the time series analysis, the results was able to provide the calculation of numerical variation in the intersection point, which is represented in 3-axis,; that we are expecting to open the way for predicting a deformation rate as well as deformation direction