• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.557-560
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• 2014

In digital communications systems, an interleaver spreads burst errors occurred in channels and makes it random errors. As a result, the signals are rearranged and encrypted to the 3rd party. Deinterleaving this unknown interleaved signal is very important in electronic warfare and various researches on reconstruction of interleaved signal have been studied in the literature. Unlike previous researches which is mainly about helical scan interleaver or bit unit interleaver, in this paper, we estimate the symbol unit convolutional interleavr and shortened Reed-Solomon code parameters such as the number of stages of interleaver, a codeword length and a data symbol length and propose an specific algorithm to obtain the parameters from the unknown interleaved signal and simulate this algorithm as well.

• Smart Structures and Systems
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• v.26 no.6
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• pp.693-701
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• 2020

The conventional Kalman Filter (KF) provides a promising way for structural state estimation. However, the physical parameters of structural systems or models should be available for the estimation. Moreover, it is not applicable when the loadings applied to the structures are unknown. To circumvent the aforementioned limitations, a two-stage KF with unknown input approach is proposed for the simultaneous identification of structural parameters and unknown loadings. In stage 1, a modified observation equation is employed. The structural state vector is estimated by KF on the basis of structural parameters identified at the previous time-step. Then, the unknown input is identified by Least Squares Estimation (LSE). In stage 2, based on the concept of sensitivity matrix, the structural parameters are updated at the current time-step by using the estimated structural states obtained from stage 1. The effectiveness of the proposed approach is numerically validated via a five-story shearing model under random and earthquake excitations. Shaking table tests on a five-story structure are also employed to demonstrate the performance of the proposed approach. It is demonstrated from numerical and experimental results that the proposed approach can be used for the identification of parameters of structure and the external force applied to it with acceptable accuracy.

• Steel and Composite Structures
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• v.34 no.5
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• pp.643-655
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• 2020

In the present work, the buckling behavior of a single-layered graphene sheet (SLGS) embedded in visco-Pasternak's medium is studied using nonlocal four-unknown integral model. This model has a displacement field with integral terms which includes the effect of transverse shear deformation without using shear correction factors. The visco-Pasternak's medium is introduced by considering the damping effect to the classical foundation model which modeled by the linear Winkler's coefficient and Pasternak's (shear) foundation coefficient. The SLGS under consideration is subjected to compressive in- plane edge loads per unit length. The influences of many parameters such as nonlocal parameter, geometric ratio, the visco-Pasternak's coefficients, damping parameter, and mode numbers on the buckling response of the SLGSs are studied and discussed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.1-11
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• 1993

This paper concentrates on models useful for analyzing the error performance of ML(Maximum Likelihood) estimators of a single unknown signal parameter: that is the error intensity model. We first develop the point process representation for the estimation error and the conditional distribution of the estimator as well as the distribution of error candidate point process. Then the error intensity function is defined as the probability dessity of the estimate and the general form of the error intensity function is derived. We then develop several intensity models depending on the way we choose the candidate error locations. For each case, we compute the explicit form of the intensity function and discuss the trade-off among models as well as the extendability to the case of multiple parameter estimation.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.6
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• pp.622-634
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• 2003

This paper is concerned with a computational method for recovering a crack shape of steam generator tubes of nuclear plants. Problems on the shape identification are discussed arising in the characterization of a structural defect in a conductor using data of eddy current inspection. A surface defect on the generator tube ran be detected as a probe impedance trajectory by scanning a pancake type coil. First, a mathematical model of the inspection process is derived from the Maxwell's equation. Second, the input and output relation is given by the approximate model by virtue of the hybrid use of the finite element and boundary element method. In that model, the crack shape is characterized by the unknown coefficients of the B-spline function which approximates the crack shape geometry. Finally, a parameter estimation technique is proposed for recovering the crack shape using data from the probe coil. The computational experiments were successfully tested with the laboratory data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1593-1600
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• 2000

A method based on frequency domain approaches is presented for the nonlinear parameters identification of structure having nonlinear joints. The finite element model of linear substructure is us ed to calculating its frequency response functions needed in parameter identification process. This method is easily applicable to a complex real structure having nonlinear elements since it uses the frequency response function of finite element model. Since this method is performed in frequency domain, the number of equations required to identify the unknown parameters can be easily increased as many as it needed, just by not only varying excitation amplitude but also selecting excitation frequencies. The validity of this method is tested numerically and experimentally with a cantilever beam having the nonlinear element. It was verified through examples that the method is useful to identify the nonlinear parameters of a structure having arbitary nonlinear boundaries.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.2
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• pp.157-178
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• 2001

In this paper, the nonlinear control of high precision pointing stabilization system using feedback-linearization design methodology based on system parameter identification is discussed. Modern nonlinear servomechanism theory is adapted to cope with the hard nonlinearities inherent in the turret system. The mathematical models of electrical turret driving system to develop a high performance control algorithm are derived, and the parameter estimation algorithm identifying the unknown system parameters such as vicious and coulomb frictions, stiffness and inertia is developed. Through computer simulation and experiments, it is shown that pointing and tracking accuracy and stabilization against the wideband stochastic disturbance induced by vehicle running on the bump course are improved. Therefore, it is considered the proposed nonlinear control technique is effective in counteracting the nonlinearities and disturbances.

• Proceedings of the KIPE Conference
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• 2004.07b
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• pp.738-741
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• 2004

The overall performance of AC servo system is greatly affected by the uncertainties of unpredictable mechanical parameter variations and external load disturbances. Therefore, to compensate this problem, it is necessary to know different parameters and load disturbances subjected to position/speed control. This paper proposes an online identification method of mechanical parameters/load disturbances for AC servo system using Support Vector Regression (SVR). The proposed methodology advocates analytic parameter regression directly from the training data, rather than adaptive controller and observer approaches commonly used in motion control applications. The experimental results demonstrate that the proposed SVR algorithm is appropriate for control of unknown servo systems even with large measurement noise.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1271-1280
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• 2000

A sensor placement technique to identify structural parameter was developed. Experimental results must be acquired to identify unknown dynamic characteristics of a targeting structure for the comparison between analytical model and real structure. If the experimental environment was not equipped itself properly, it can be happened that some valuable information are distorted or ill-condition can be occurred. In this work the index to determine exciting points was derived from the criterion of maximizing parameter sensitivity matrix and that to choose measurement points was from that of preserving the invariant of sensitivity matrix. This idea was applied to a compressor hull structure to verify its performance. The result shows that the selection of measurement and excitation points using suggested criteria improve the ill-conditioning problem of inverse type problems such , as model updating.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.645-655
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• 2011

Chandrasekar et al. (2004) introduced a generalized Type-II hybrid censoring. In this paper, we propose generalized doubly Type-II hybrid censoring. In addition, this paper presents the statistical inference on the scale parameter for the half logistic distribution when samples are generalized doubly Type-II hybrid censoring. The approximate maximum likelihood(AMLE) method is developed to estimate the unknown parameter. The scale parameter is estimated by the AMLE method using two di erent Taylor series expansion types. We compar the AMLEs in the sense of the mean square error(MSE). The simulation procedure is repeated 10,000 times for the sample size n = 20; 30; 40 and various censored samples. The $AMLE_I$ is better than $AMLE_{II}$ in the sense of the MSE.