• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.382-384
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• 2004

In this parer, we propose a clustering that perform algorithm using new convergence properties. For detection and optimization of cluster, we use to similarity measure with cumulative probability and to inference the its parameters with MLE. A merits of using the cumulative probability in our method is very effectiveness that robust to noise or unnecessary data for inference the parameters. And we adopt similarity threshold to converge the number of cluster that is enable to past convergence and delete the other influence for this learning algorithm. In the simulation, we show effectiveness of our algorithm for convergence and optimization of cluster in riven data set.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.73-76
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• 2001

It is well-known that the convergence rate gets worse when an input signal to an adaptive filter is correlated. In this paper we propose a new adaptive filtering algorithm that makes the convergence rate highly improved even for highly correlated input signals. By introducing an orthogonal constraint between successive input signal vectors, we overcome the slow convergence problem caused by the correlated input signal. Simulation results show that the proposed algorithm yields highly improved convergence speed and excellent tracking capability under both time-invariant and time varying environments, while keeping both computation and implementation simple.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.327-329
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• 1992

This Paper presents an algorithm for improvement of convergence in Adaptive Filter. The proposed algorithm employes the time-varying Convergence Factor to Block LMS adaptation algorithm. Computer simulation for Adaptive Modeling of time-invarying and time-varying unknown systems has been performed. Performance comparisons between LMS, BLMS algorithms which have fixed Convergence factors obtained by trial and error and the proposed algorithm which has time-varying Convergence Factor show that the proposed algorithm is superior to LMS and BLMS algorithm with respect to speed and accuracy of adaptation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.939-951
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• 1994

In adaptive equalizers based on least mean squares (LMS) algorithms, the convergence rate is determined by the convariance matrix of an input signal. When the eigenvalue spread of the convariance matrix is close to unity, the convergence rate is quite fast. In this paper, for fast convergence of LMS-based adaptive equalizers we propose a modified reference signal pertinent to the statistical channel. From the theoretical analysis and computer simulation, it is shown that the proposed modification method is quite effective for fast convergence of LMS-based adaptive equalizers.

• ETRI Journal
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• v.30 no.4
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• pp.600-602
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• 2008

A very small patch-type RFID tag antenna (UHF band) using ceramic material mountable on metallic surfaces is presented. The size of the proposed tag is 25 mm${\times}$25 mm${\times}$3 mm. The impedance of the antenna can be easily matched to the tag chip impedance by adjusting the size of the shorting plate of the patch and the size of the feeding loop. The measured maximum reading distance of the tag at 910 MHz was 5 m when it was mounted on a 400 mm${\times}$400 mm metallic surface. The proposed design is verified by simulation and measurements which show good agreement.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.629-635
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• 1999

A second-order iterative learning control algorithm with feedback is proposed in this paper, in which a feedback term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances or system parameter variations. The convergence proof of the proposed algorithm is givenl, and the sufficient condition for the convergence of the algorithm is provided. And it also includes the discussions about the convergence performance of the algorithm when the initial condition at the beginning of each iteration differs from the previous value of the initial. Simulation results show the validity and efficiency of the proposed algorithm.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.68-77
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• 2002

EM algorithm has good convergence rate for numerical procedures which converges on very small step. In the case of proportion estimation in a mixed distribution which has very big incomplete data or of update of new data continuously, however, EM algorithm highly depends on a initial value with slow convergence ratio. There have been many studies to improve the convergence rate of EM algorithm in estimating the proportion parameter of a mixed data. Among them, dynamic EM algorithm by Hurray Jorgensen and Titterington algorithm by D. M. Titterington are proven to have better convergence rate than the standard EM algorithm, when a new data is continuously updated. In this paper we suggest dynamic EM algorithm and Titterington algorithm for the estimation of a mixed Poisson distribution and compare them in terms of convergence rate by using a simulation method.

• Korean Journal of Agricultural Science
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• v.45 no.1
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• pp.120-127
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• 2018

The rural labor force has gradually been decreasing due to the decrement of the farm population and the increment of the aging population. To solve these problems, it is necessary to develop and study autonomous agricultural machinery. Therefore, analyzing the dynamic behavior of vehicles in an autonomous agricultural environment is important. Until now, most studies on agricultural machinery, especially on ground vehicle dynamics, have been done by field tests. However, these field test methods are time consuming and costly with seasonal restrictions. A research method that can replace existing field test methods by using simulations is needed. In this study, we did basic research analyzing the effect of the travelling speed of a tractor on tire slip using simulation software. A tractor simulation model was developed based on field conditions following a straight path. The simulation was done for three ranges of speed: 20 - 30 km/h (considered the normal travelling speed range), 6 - 8 km/h (considered the plow tillage speed range) and 2 - 4 km/h (considered the rotary tillage speed range). The results of the simulation show that the slip ratio and slip angle values tended to increase as the traveling speed range of the tractor decreased. From the simulation results, it can be concluded that at low tractor speeds, it becomes more difficult to control the vehicle path. In future research, simulations will be done with various work environments such as a curved path as well as with various friction coefficient conditions, and the simulation results will be experimentally verified by applying them to an agricultural tractor.

• Membrane Journal
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• v.30 no.4
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• pp.242-251
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• 2020

Computer simulation tools mainly used for polymer materials and polymeric membranes are divided into various fields depending on the size of the object to be simulated and the time to be simulated. The computer simulations introduced in this review are classified into three categories: Quantum mechanics (QM), molecular dynamics (MD), and mesoscale modeling, which are mainly used in computational material chemistry. The computer simulation used in polymer research has different research target for each kind of computational simulation. Quantum mechanics deals with microscopic phenomena such as molecules, atoms, and electrons to study small-sized phenomena, molecular dynamics calculates the movement of atoms and molecules calculated by Newton's equation of motion when a potential or force of is given, and mesoscale simulation is a study to determine macroscopically by reducing the computation time with large molecules by forming beads by grouping atoms together. In this review, various computer simulation programs mainly used for polymers and polymeric membranes divided into the three types classified above will be introduced according to each feature and field of use.

• Journal of Radiation Protection and Research
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• v.42 no.1
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• pp.48-55
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• 2017

Background: Simultaneous detection of neutrons and gamma rays have become much more practicable, by taking advantage of good gamma-ray discrimination properties using pulse shape discrimination (PSD) technique. Recently, we introduced a commercial CLYC system in Korea, and performed an initial characterization and simulation studies for the CLYC detector system to provide references for the future implementation of the dual-mode scintillator system in various studies and applications. Materials and Methods: We evaluated a CLYC detector with 95% $^6Li$ enrichment using various gamma-ray sources and a $^{252}Cf$ neutron source, with validation of our Monte Carlo simulation results via measurement experiments. Absolute full-energy peak efficiency values were calculated for gamma-ray sources and neutron source using MCNP6 and compared with measurement experiments of the calibration sources. In addition, behavioral characteristics of neutrons were validated by comparing simulations and experiments on neutron moderation with various polyethylene (PE) moderator thicknesses. Results and Discussion: Both results showed good agreements in overall characteristics of the gamma and neutron detection efficiencies, with consistent ~20% discrepancy. Furthermore, moderation of neutrons emitted from $^{252}Cf$ showed similarities between the simulation and the experiment, in terms of their relative ratios depending on the thickness of the PE moderator. Conclusion: A CLYC detector system was characterized for its energy resolution and detection efficiency, and Monte Carlo simulations on the detector system was validated experimentally. Validation of the simulation results in overall trend of the CLYC detector behavior will provide the fundamental basis and validity of follow-up Monte Carlo simulation studies for the development of our dual-particle imager using a rotational modulation collimator.