• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.6
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• pp.655-663
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• 2021

In this paper, DFT-Based channel estimation with channel response mirroring is proposed and analyzed. In General, pilot symbols for channel estimation in MIMO(Multi-Input Multi-Output) OFDM(Orthogonal Frequency-Division Multiplexing) Systems have a diamond shape in the time-frequency plane. An interpolation technique to estimate the channel response of sub-carriers between reference symbols is needed. Various interpolation techniques such as linear interpolation, low-pass filtering interpolation, cubic interpolation and DFT interpolation are employed to estimate the non-pilot sub-carriers. In this paper, we investigate the conventional DFT-based channel estimation for noise reduction and channel response interpolation. The conventional method has performance degradation by distortion called "edge effect" or "border effect". In order to mitigate the distortion, we propose an improved DFT-based channel estimation with channel response mirroring. This technique can efficiently mitigate the distortion caused by the DFT of channel response discontinuity. Simulation results show that the proposed method has better performance than the conventional DFT-based channel estimation in terms of MSE.

• The Journal of the Acoustical Society of Korea
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• v.9 no.2
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• pp.61-69
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• 1990

We have investigated the digital bit synchronization problem in baseband communication receiver systems using the Gauss-Markov estimation technique which is equivalent to the weighted least square method. The realized bit synchronizer, including the data detector, processes the input signal two dimensionally into the transition phase and data level under the white Gaussian noise environment. We have confirmed the relization of the bit synchronizer via computer simulation. In addition, we have compared and evaluated the estimation error performance of the proposed method with that of the conventional DTTL method and of the minimum likelihood method.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.47-51
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• 2005

Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1037-1041
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• 1996

Input-output linearization technique in nonlinear control does not guarantee the robustness in the presence of parameter uncertainty or unmodeled dynamics, etc. However, it has been used as an important preliminary step in achieving additional control objectives, for instance, robustness to parameter uncertainty and disturbance attenuation. An indirect adaptive control scheme based on input-output linearization is proposed in this paper. The scheme consists of a Hopfield network for process parameter identification and an adaptive sliding mode controller based on input-output linearization, which steers the system response into a desired configuration. A numerical example is presented for the trajectory tracking of uncertain nonlinear dynamic systems with slowly time-varying parameters.

• 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.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.6
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• pp.746-752
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• 2006

This paper presents a scheme for the parameter estimation and stabilization of unstable systems, such as inverted pendulum systems. First a stable feedback loop is constructed for an inverted pendulum system and then its parameters are estimated based on input-output data, a real-coded genetic algorithm(RCGA) and the model adjustment technique. Then, a PI-type LQ control scheme is designed based on the estimated model. The performance of the proposed algorithm is demonstrated through a set of simulation and experiment.

• Geotechnical Engineering
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• v.8 no.4
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• pp.41-50
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• 1992

In general, the conceptual lumped-parameter groundwater flow model to predict the groundwater fluctuations in hillside slopes has unknown model parameters to be estimated from the known input -output data. The purpose of this study is to estimate the optimal model parameters of the groundwater flow model developed by authors. The Mazilnum A Posteriori( MAP) estimation method is utilized for this purpose and it is applied to a site which shows the typical landslide in Korea. The result of application shows tllat the 반AP estimation method can estimate the unknown parameters properly well. The groundwater model developed along with estimation technique applied in this paper will be used for assessing risk of landslides.

• ETRI Journal
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• v.37 no.4
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• pp.772-779
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• 2015

This paper presents a power-efficient hardware realization for a motion estimation technique that is based on the full-search block matching algorithm (FSBMA). The considered input is the quarter common intermediate format of digital video. The mean of absolute difference (MAD) is the distortion criteria employed for the block matching process. The conventional architecture considered for the hardware realization of FSBMA is that of the shift register-based 2-D systolic array. For this architecture, a conservative approximation technique is adapted to eliminate unnecessary MAD computations involved in the block matching process. Upon introducing the technique to the conventional architecture, the power and complexity of its implantation is reduced, while the accuracy of the motion vector extracted from the block matching process is preserved. The proposed architecture is verified for its functional specifications. A performance evaluation of the proposed architecture is carried out using parameters such as power, area, operating frequency, and efficiency.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.641-649
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• 2010

Estimation of uncertain parameters is required in many engineering problems which involve probabilistic structural analysis as well as prognosis of existing structures. In this case, Bayesian framework is often employed, which is to represent the uncertainty of parameters in terms of probability distributions conditional on the provided data. The resulting form of distribution, however, is not amenable to the practical application due to its complex nature making the standard probability functions useless. In this study, Markov chain Monte Carlo (MCMC) method is proposed to overcome this difficulty, which is a modern computational technique for the efficient and straightforward estimation of parameters. Three case studies that implement the estimation are presented to illustrate the concept. The first one is an inverse estimation, in which the unknown input parameters are inversely estimated based on a finite number of measured response data. The next one is a metamodel uncertainty problem that arises when the original response function is approximated by a metamodel using a finite set of response values. The last one is a prognostics problem, in which the unknown parameters of the degradation model are estimated based on the monitored data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.51-64
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• 2004

This paper proposes an algerian of generating a tuner-template from multiple fingerprint impressions using a data fusion technique for fingerprint enrollment. The super-template is considered as a single fingerprint template which contains most likely true minutiae based on multiple fingerprint images. The proposed algorithm creates the super template by utilizing a recursive Bayesian estimation method (RBEM), which assumes a sequential fingerprint input model and estimates the credibility of the minutiae in previous input templates froma current input template. Consequently. the RBEM assigns a higher credibility to commonly detectable minutiae from several input templates and a lower credibility to rarely found minutiae from other input templates. Likewise, the RBEM is able to estimate a credibility of the minutia type (ridge ending or bifurcation). Preliminary experiments demonstrate that, as the number of fingerfrint images increases, the performance of recognition can be improved while maintaining the processing time and the size of memory storage for tile super-template almost constant.