• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.6
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• pp.564-571
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• 2015

In this paper, we propose a multiple-input, multiple-output(MIMO) interferometric radar network system to generate three-dimensional (3-D) MIMO interferometric inverse synthetic aperture radar(InISAR) image. In the MIMO interferometric radar network system, the MIMO InISAR image can be formed by an incoherent summation of multiple bistatic InISAR images that show 3-D scatterers of a target observed at different bistatic interfermetric configurations, respectively. Because bistatic-sccattering physics of a target at different viewpoints are visible in the 3-D MIMO InISAR image, it can provide various scatterering physics properties of a target, and can be used for target classification as a useful feature vector. Simulations validate that our proposed method successfully finds locations of scatterers of a target in MIMO radar interferometric network system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.57-65
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• 2022

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU's input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.179-185
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• 2010

In a sensitivity analysis, an uncertainty importance measure is often used to assess how much uncertainty of an output is attributable to the uncertainty of an input, and thus, to identify those inputs whose uncertainties need to be reduced to effectively reduce the uncertainty of output. A function is called monotonic if the output is either increasing or decreasing with respect to any of the inputs. In this paper, for a monotonic function, we propose a method for evaluating the measure which assesses the expected percentage reduction in the variance of output due to ascertaining the value of input. The proposed method can be applied to the case that the output is expressed as linear and nonlinear monotonic functions of inputs, and that the input follows symmetric and asymmetric distributions. In addition, the proposed method provides a stable uncertainty importance of each input by discretizing the distribution of input to the discrete distribution. However, the proposed method is computationally demanding since it is based on Monte Carlo simulation.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.512-517
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• 2001

In this paper, a wide input range active multi-pulse rectifier for utility interface of power electronic converters is proposed. The scheme combines multi-pulse method using a V-A transformer and boost rectifier modules. A current control scheme for the rectifier modules is proposed to achieve sinusoidal line currents in the utility input over a wide input range of input voltage and output load conditions. A design example is included for a 208V to 460V input, $700V_{dc}$ do 10kW output rectifier system. Simulation results are shown.

• Journal of Power Electronics
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• v.13 no.4
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• pp.609-618
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• 2013

This paper proposes a primary side constant power control scheme for TRIAC dimmer compatible LED drivers. The LED driver is a Flyback converter operated in boundary conduction mode (BCM) to minimize the switching loss. With the proposed control scheme, the input power of the Flyback converter can be controlled by the TRIAC dimming angle, which is not affected by AC input voltage variations. Since the output voltage is almost constant for LED loads, the output current can be changed by controlling the input power with a given conversion efficiency. The isolated feedback circuit is eliminated with the proposed primary side control scheme, which dramatically simplifies the whole circuit. In addition, the input current automatically follows the input voltage due to the BCM operation, and the resistive input characteristic can be achieved which is attractive for TRIAC dimming applications. Experimental results from a 15W prototype verify the theoretical analysis.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.239-246
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• 2003

Statisticians, or data miners, are often requested to assess the importances of input variables in the given supervised learning model. For the purpose, one may rely on separate ad hoc measures depending on modeling types, such as linear regressions, the neural networks or trees. Consequently, the conceptual consistency in input variable importance measures is lacking, so that the measures cannot be directly used in comparing different types of models, which is often done in data mining processes, In this short communication, we propose a unified approach to the importance measurement of input variables. Our method uses sensitivity analysis which begins by perturbing the values of input variables and monitors the output change. Research scope is limited to the models for continuous output, although it is not difficult to extend the method to supervised learning models for categorical outcomes.

• ETRI Journal
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• v.29 no.1
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• pp.89-94
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• 2007

A mathematical model for the input-output characteristic of an amplifier exhibiting gain expansion and weak and strong nonlinearities is presented. The model, basically a Fourier-series function, can yield closed-form series expressions for the amplitudes of the output components resulting from multisinusoidal input signals to the amplifier. The special case of an equal-amplitude two-tone input signal is considered in detail. The results show that unless the input signal can drive the amplifier into its nonlinear region, no gain expansion or minimum intermodulation performance can be achieved. For sufficiently large input amplitudes that can drive the amplifier into its nonlinear region, gain expansion and minimum intermodulation performance can be achieved. The input amplitudes at which these phenomena are observed are strongly dependent on the amplifier characteristics.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.157-165
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• 1995

In this paper the comparison between the neural networks and traditional approaches as nonlinear system identification methods are considered. Two model structures of neural networks are the state space model and the input output model neural networks. The traditional methods are the AutoRegressive eXogeneous Input model and the Nonlinear AutoRegressive eXogeneous Input model. Computer simulation for an analytic dynamic model of a single input single output nonlinear system has been done for all the chosen models. Model validation for the obtained models also has been done with testing inputs of the sinusoidal, ramp and the noise ramp.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2033-2036
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• 1997

In this paper, we proposed a novel current-fed DC-DC converter with multi-output. It has two winding reactor in series with the input source of the converter. By using the 2nd winding recycling the energy stored in the reactor to the input, the double-outputs DC-DC converter can be created, which makes it a good choice for a multi-output power supply with more outputs and has savings in cost and space. The steady state and dynamic characteristics of the converter are analyzed in detail by using the state space averaging method. It is found that the maximum value of $V_{o2}$ exists in the 2nd output and also during the MOSFET off period, the energy stored in the magnetizing inductance is reset through auxiliary winding $N_3$, so the duty cycle is restricted to 50%. Theoretical and experimental results were taken from the converter rated at switching frequency 50kHz. input voltage 50V. output voltage 5V. 12V and output power 65W. As a result, both results were well consistent. Therefore, it is varified the validity of the proposed converter in this paper.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.578-581
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• 1996

A torque trajectory control of the IPM synchronous motor using an adaptive input-output linearization technique is proposed. The input-output linearization is performed using the estimated torque output with the knowledge of machine parameters. The linearized model gives the output torque error under the variation of the flux linkage. To give a good torque tracking in the presence of the flux linkage variation, the flux linkage will be estimated where the adaptation law h derived by the Popov's hyperstability theory and the positivity concept. This estimated value is also used for the generation of the d-axis current command for the maximum torque control. Thus, a good torque tracking and the exact maximum torque-per-current operation will be obtained.