• 한국전자파학회논문지
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• 제26권6호
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• pp.564-571
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• 2015

본 논문에서는 다중입력-다중출력(multiple-input, multiple-output: MIMO) 간섭계(interferometric) 레이다 네트워크 시스템을 기반한 MIMO 간섭계 역합성 개구면 레이다(inverse synthetic aparture radar: InISAR) 영상 형성기법에 관해 연구하였다. MIMO 간섭계 레이다 네트워크 시스템 내에서는 여러 바이스태틱 InISAR 영상들이 형성되며, 이들을 인코히리언트(incoherent)하게 합성함으로써 MIMO InISAR 영상을 형성할 수 있다. 여기서, 바이스태틱 InISAR 영상은 바이스태틱 기하구조 내에서의 표적에 대한 산란분포를 3차원의 형태로 도시한다. 상기 MIMO InISAR 영상에서는 다중 각도에서의 바이스태틱 산란 현상을 3차원의 형태로 도시하기 때문에, 표적의 다양한 산란 정보를 제공함과 더불어, 표적 식별 시 유용한 특징 벡터(feature vector)로써 활용될 수 있다. 시뮬레이션을 통해, 제안된 MIMO InISAR 영상 형성 기법을 이용함으로써 표적에 대한 다중각도에서의 바이스태틱 산란분포가 3차원의 형태로 도시되는 것을 확인할 수 있다.

• 산업경영시스템학회지
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• 제45권3호
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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.

• 한국산업정보학회논문지
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• 제15권5호
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• pp.179-185
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• 2010

시스템의 민감도 분석을 위한 불확실성 중요도 측도란 어떠한 입력변수의 불확실성이 반응변수의 불확실성에 미치는 영향의 정도를 평가하여, 반응변수의 불확실성을 감소시키기 위해서는 어떤 입력변수들의 불확실성을 감소시키는 것이 효과적인지를 밝히는데 사용된다. 본 논문에서는 입력변수와 반응변수 간의 관계식이 단조함수일 때, 어떤 입력변수의 불확실성이 제거될 때 반응변수 분산의 기대되는 감소량을 백분율로 측정하는 측도를 평가하기 위한 방법을 제안한다. 제안된 평가 방법은 입력변수와 반응변수 간의 관계식이 선형 및 비선형 단조함수 모두에 적용될 수 있으며 입력변수의 분포에 제한이 없으며, 입력변수의 분포를 이산형 분포로 근사화하는 기법을 사용함으로써 불확실성 중요도 측도의 안정적인 추정치를 얻을 수 있다 반면에 제안된 평가 방법은 몬테칼로 시뮬레이션을 기반으로 하기 때문에 계산량이 많은 단점이 있다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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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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• 제13권4호
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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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• 제10권1호
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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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• 제29권1호
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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.

• 한국정밀공학회지
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• 제12권5호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 F
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 A
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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.