• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1217-1224
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• 2005

To improve the accuracy of a metamodel, additional sample points can be selected by using a specified criterion, which is often called sequential sampling approach. Sequential sampling approach requires small computational cost compared to one-stage optimal sampling. It is also capable of monitoring the process of metamodeling by means of identifying an important design region for approximation and further refining the fidelity in the region. However, the existing critertia such as mean squared error, entropy and maximin distance essentially depend on the distance between previous selected sample points. Therefore, although sufficient sample points are selected, these sequential sampling strategies cannot guarantee the accuracy of metamodel in the nearby optimum points. This is because criteria of the existing sequential sampling approaches are inefficient to approximate extremum and inflection points of original model. In this research, new sequential sampling approach using the sensitivity of metamodel is proposed to reflect the response. Various functions that can represent a variety of features of engineering problems are used to validate the sensitivity approach. In addition to both root mean squared error and maximum error, the error of metamodel at optimum points is tested to access the superiority of the proposed approach. That is, optimum solutions to minimization of metamodel obtained from the proposed approach are compared with those of true functions. For comparison, both mean squared error approach and maximin distance approach are also examined.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2002.11a
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• pp.44-48
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• 2002

This paper describes an adaptive signal processing of digital receiver with DDC(Digital Down Convertor), DDC is implemented by using NCO(Numerically Controlled Oscillator), digital low pass filter. for the passband sampling, we present the results of digital receiver simulation with DDC. We confirm that the low IP signal is converted to zero IF by DDC. DOA(Direction Of Arrival) estimation technique using MUSIC(Multiple SIgnal Classification) algorithm with high resolution is presented. We Cow that an accurate resolution of DOA depends on the input sampling number.

• ETRI Journal
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• v.34 no.3
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• pp.369-378
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• 2012

In this paper, we propose new adaptive search range motion estimation methods where the search ranges are constrained by the probabilities of motion vector differences and a search point sampling technique is applied to the constrained search ranges. Our new methods are based on our previous work, in which the search ranges were analytically determined by the probabilities. Since the proposed adaptive search range motion estimation methods effectively restrict the search ranges instead of search point sampling patterns, they provide a very flexible and hardware-friendly approach in motion estimation. The proposed methods were evaluated and tested with JM16.2 of the H.264/AVC video coding standard. Experiment results exhibit that with negligible degradation in PSNR, the proposed methods considerably reduce the computational complexity in comparison with the conventional methods. In particular, the combined method provides performance similar to that of the hybrid unsymmetrical-cross multi-hexagon-grid search method and outstanding merits in hardware implementation.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1544-1550
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• 2014

In this paper, an adaptive optimization strategy utilizing Kriging model and genetic algorithm is proposed for the optimal design of electromagnetic devices. The ordinary Kriging assisted by the spherical covariance model is used to construct surrogate models. In order to improve the computational efficiency, the adaptive uniform sampling strategy is applied to generate sampling points in design space. Through several iterations and gradual refinement process, the global optimal point can be found by genetic algorithm. The proposed algorithm is validated by application to the optimal design of a switched reluctance motor, where the stator pole face and shape of pole shoe attached to the lateral face of the rotor pole are optimized to reduce the torque ripple.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.713-723
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• 2013

An objective Bayesian estimation procedure of the two-parameter Pareto distribution is presented under the reference prior and the noninformative prior. Bayesian estimators are obtained by Gibbs sampling. The steps to generate parameters in the Gibbs sampler are from the shape parameter of the gamma distribution and then the scale parameter by the adaptive rejection sampling algorism. A numerical study shows that the proposed objective Bayesian estimation outperforms other estimations in simulated bias and mean squared error.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.540-545
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• 1988

In this study a microcomputer-aided design program has been developed to design and analysis for the digital adaptive control system. DACS(Digital Adaptive Control System) program has been written in GWBASIC language which is suitable for IBM-PC compatible. The dynamics of each element was modulized and described by linear difference equations. By the aid of this program, sampling time, the number of bits of A/D and D/A converter and the stability for the digital adaptive control system can be determined. In order to estimate the system parameters an on-line identification and a regression analysis method are utilized. The simulation results have been well agreed with the experiments. To demonstrate the utility of this program, an adaptive control system has been designed for air-heating system.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.421-424
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• 2008

The real time modeling of dynamic system on adaptive control system is very important for flying control system(FCS). Using traditional method, it is required much calculation load for integral/differential at control system. Therefore, It is very important theme of study in these days to find algorithms for integration/differential at FCS. These algorithms for integral/differential influence strongly stability/reliability to control flying object. In this paper, we present optimal predictive sampling time for reduce calculation load at FCS and optimal predictive time on general cost function by applying adaptive control method.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.27-30
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• 2007

This paper deals with an equivalent circuit model for RF passive components. Rational functions are obtained from the frequency responses of EM simulation by using Foster canonical partial fraction expressions. The Vector Fitting(VF) and the Adaptive Frequency Sampling(AFS) scheme are also implemented to obtain the rational functions. A passivity enforcement algorithm is applied to ensure the stability of the equivalent circuit model. In order to verify the schemes, S parameters of the equivalent circuit model is compared to those of EM simulation in case of the microstrip line structure with 3 slots in ground.

• Journal of Electrical Engineering and Technology
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• v.6 no.3
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• pp.408-413
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• 2011

In this paper, a real-coefficient approach to Adaptive Frequency Sampling (AFS) technique is developed for efficient equivalent circuit modeling of RF components. This proposed method is advantageous than the vector fitting technique and the conventional AFS method in terms of fewer samples leading to a lower order of a rational function on a given data and to a direct conversion to an equivalent circuit for PSPICE(Personal Simulation Program with Integrated Circuit Emphsis) simulation, respectively. To validate the proposed method, the distributed equivalent circuit of a presented multi-layered RF low-pass filter is obtained using the proposed real-coefficient AFS, and then comparisons with EM simulation and circuit simulation for the device under consideration are achieved.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.31-36
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• 2020

Most of the background subtraction algorithms show good performance in static scenes. In the case of dynamic scenes, they frequently cause false alarm to "temporal clutter", a repetitive motion within a certain area. In this paper, we propose a robust technique for the multiple interval pixel sampling (MIS) algorithm to handle highly dynamic scenes. An adaptive threshold scheme is used to suppress false alarms in low-confidence regions. We also utilize multiple background models in the foreground segmentation process to handle repetitive background movements. Experimental results revealed that our approach works well in handling various temporal clutters.