• IEIE Transactions on Smart Processing and Computing
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• v.3 no.5
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• pp.267-270
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• 2014

This paper presents the comparative performance of an adaptive FIR filter for a Delayed LMS algorithm. The delayed error signal was used to obtain a Delayed LMS algorithm to allow efficient pipelining for achieving a small critical path and area efficient implementation. This paper presents hardware efficient results (device utilization parameters) and power consumed. The FPGA families (Artix-7, Virtex-7, and Kintex-7) for a low voltage perspective are shown. The synthesis results showed that the artix-7 CMOS family achieves the lowest power consumption of 1.118 mW with 83.18 % device utilization. Different Precision strategies, such as the speed optimization and power optimization, were imposed to achieve these results. The algorithm was implemented using MATLAB (2013b) and synthesized on the Leonardo spectrum.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.363-368
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• 2008

In this paper, the Resistive Companion Form(RCF) analysis method is applied to analyze small signal stability of power systems including thyristor controlled FACTS equipments such as SVC. The eigenvalue sensitivity analysis algorithm in discrete systems based on the RCF analysis method is presented and applied to the power system including SVC. As a result of simulation, the RCF analysis method is proved very effective to precisely calculate the variations of eigenvalues or newly generated unstable oscillation modes after periodic switching operations of SVC. Also the eigenvalue sensitivity analysis method based on the RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of controller parameters about the dominant oscillation mode after periodic switching operations in discrete systems. These simulation results are different from those of the conventional continuous system analysis method such as the state space equation and proved that the RCF analysis method is very effective to analyze the discrete power systems including periodically operated switching equipments such as SVC.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.503-515
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• 1998

When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector, it follows approximately Poisson distribution. Under the four assumptions in the presence of errors and uncertainties for the Poisson parameters, an exact probability distribution of neutral particles have been derived. The probability distribution for the neutron signals received by a detector averaged over the three sources of errors is expressed as a four-dimensional integral of certain data. Two of the four integrals can be evaluated analytically and thereby the integral is reduced to a two-dimensional integral. The monotone likelihood ratio(MLR) property of the distribution is proved by using the Cauchy mean value theorem for the univariate distribution and multivariate distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem related to the distribution.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.749-753
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• 2007

The purpose of this study is to design of a linear feeder using a multi body dynamic program, and to analyze a dynamic motion of the feeder that can transport small mechanical parts uniformly. In order to establish the analysis model of the linear feeder, each parts of the feeder are divided into two types which the rigid and flexible body. For the dynamic simulation, RecurDyn, which is a commercial multi-body dynamic package, is used. We also consider the design parameters for optimal dynamic motion such as centroid, stiffness, and mass of the feeder system. In order to analyze the dynamic motion of a linear feeder, the displacements of the feeder are measured by several accelerometers when it is in an operating condition. After the signal data from the accelerometers are captured in the time domain, the dynamic motion in the space is visualized by using graphic computer software.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.993-998
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• 2002

watches, air bearings and printed circuit hoards (PCB). However, it is not easy to determine optimum cutting conditions since the micro drilling process is very sensitive to various disturbances. Also, undesirable characteristics to optimize the micro drilling are small signal-to-noise ratios, drill wandering motions and high aspect ratios. Thus, in this study, experimental design methods are applied to determine optimum cutting conditions. Suing the methods, three cutting parameters, fred, step and curving speed are optimized to minimize thrust forces. Obtained conditions are verified through required experimental works. As the results, it is shown that the experimental methods can be applied to micro drilling processes to determine Optimum Cutting Conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.7
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• pp.628-639
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• 1991

A new efficient method for GaAs MESFET model parameter extraction is proposed, which is based on the bias dependance of each parameter characteristics derved from the analytic model. The requiremnts of the method are only small-signal S-parameter measurements under the three bias variations. Fixation of the linear model parameter values in the optimization process is made using the sensitivity information of the model parameter obtained by the weighted Broyden update method, it is to improve the uniqueness and reliablility of the solution. The validity of the extracted values of the FET model parameters is confirmed by comparing the simulation results with the experimental data.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.3
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• pp.182-188
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• 2006

An artificial neural network model for the microwave characteristics of an InGaAs/InP hemt for 70 nm gate length has been developed. The small-signal microwave parameters have been evaluated to determine the transconductance and drain-conductance. We have further investigated the frequency characteristics of the device. The neural network training have been done using the three layer architecture using Levenberg-Marqaurdt Backpropagation algorithm. The results have been compared with the experimental data, which shows a close agreement and the validity of our proposed model.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.3
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• pp.210-224
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• 2006

A new analytical model for the static I-V characteristics of GaAs MESFET’s under optically controlled conditions in both linear and saturation region is presented in this paper. The novelty of the model lies in characterizing both photovoltaic (external, internal) and photoconductive effects. Deep level traps in the semi insulating GaAs substrate are also included in this model. Finally, effect of backgate voltage on I-V characteristics is explained analytically for the first time in literature. Small signal parameters of GaAs MESFET are derived under both dark and illuminated conditions. Some of the results are compared with reported experimental results to show the validity of the proposed model. Since accurate dc modeling is the key to accurate ac modeling, this model is very useful in the designing of photonic MMIC’s and OEIC’s using GaAs MESFET.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2001.11a
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• pp.257-261
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• 2001

This paper presents the implementation of wide-band RFIC amplifier operating from near 50MHz to 3GHz using Tachyonics SiGe HBT foundry. Voltage shunt feedback is used for the flat gain and the broad band impedance matching. Initial design parameters are calculated using the low frequency small signal analysis. Since the HBT model was not available at the design time, discrete tuning board was made for fine tuning in the low frequency range. Fabricated amplifier shows 12dB gain with 1dB fluctuation and PldB reaches 15dBm at 850MHz.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.167-170
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• 2002

This paper presents a mode estimation for the analysis of small signal stability in power system. The low frequency oscillation mode estimation is based on Prony method that is able to accurately compute the modal parameters (frequency and damping) of oscillation mode from time series. The time series or time domain data is obtained in TSA process. The method applied to a large scale power systems and compared on the eigenanalysis results.