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정태균,이용복,강성진,Jung, Tae-Kyun,Lee, Yong-Bok,Kang, Sung-Jin 한국국방경영분석학회 2010 한국국방경영분석학회지 Vol.36 No.1
In Korea weapon system acquisition processes, it's required a cost estimation report obtained from a commercial cost model. The PRICE model is generally used as a cost estimation model in Korea. However, the model uses American historical R&D data and it's output cost component is different from our cost component of defense accounting system. Also, we found that estimating results show about 10% of difference when we comparing with actual costs in 44 finished weapon acquisition projects. There are some limitations in calibration to increase an accuracy of the PRICE model because it's difficult obtain good real input data, detailed cost and technical data in low level WBS. So, only 8% of the defense R&D projects are calibrated and validation of calibration results is more difficult. Therefore, we studied the standard calibration process and performed the calibration about the MCPLXS/E parameters of the PRICE model based on actual cost data. In order to obtain a good calculation result, we collected the actual material costs from the defense industry companies. Our results can be used for an reference in similar weapon system R&D and production cost estimation cases.
정태균,박동철 명지대학교 대학원 1999 대학원논문집 Vol.3 No.-
Equalization of satellite communication using Complex-Bilinear Recurrent Neural Network(C-BLRNN) is proposed in this paper. Since the BLRNN is based on the bilinear polynomial it has been more effectively used in modeling highly nonlinear systems with time-series characteristics than multi-layer perceptron type neural networks(MLPNN). The BLRNN is first expanded to its complex value version(C-BLRNN) for dealing with the complex input values C-BLRNN is then applied to equalization of a digital satellite communication channel for M-PSK and QAM, which has severe nonlinearity with memory due to TWTA(Traveling Wave Tube Amplifier). The proposed C-BLRNN based equalizer for a channel model is compared with currently used Volterra filter Equalizer. DFE, and conventional Complex MLPNN Equalizer. The results show that the proposed C-BLRNN based equalizer gives very favorable results in both of MSE and BER criteria over Volterra filter Equalizer, DFE, and Complex MLPNN Equalizer.
박동철,정태균 明知大學校 産業技術硏究所 1999 産業技術硏究所論文集 Vol.18 No.-
Equalization of satellite communication using Complex-Bilinear Recurrent Neural Network(C-BLRNN) is proposed in this paper. Since the BLRNN is based on the bilinear polynomial, it has been more effectively used in modeling highly nonlinear systems with time-series characteristics than multi-layer perception type neural networks(MLPNN). The BLRNN is first expanded to its complex value version(C-BLRNN) for dealing with the complex input values. C-BLRNN is then applied to equalization of a digital satellite communication channel for M-PSK and QAM, which has severe nonlinearity with memory due to TWTA(Traveling Wave Tube Amplifier). The proposed C-BLRNN based equalizer for a channel model is compared with currently used Volterra filter Equalizer, DFE, and conventional Complex MLPNN Equalizer. The results show that the proposed C-BLRNN based equalizer gives very favorable results in both of MSE and BER criteria over Volterra filter Equalizer, DFE, and Complex MLPNN Equalizer.
전자제어 Motorcycle Engine을 컨트롤하기 위한 제어 Algorithm 분석
정태균(Tae-Gyun Jung) 산업기술교육훈련학회 2009 산업기술연구논문지 (JITR) Vol.14 No.3
We have developed carburetors to control motorcycle engines for many years, but the fuel economy and the emissions of those engines have not been good. So, it is significance to develope a ECU system for small gasoline engine to be used on the motorcycle. An ECU with 16bit microprocessor has been developed and used to control a motorcycle engine. In this paper, we studied about control algorithm of motorcycle engine to supply to a real one. This system is consisting of hardware and software for more precise control on fuel injection, ignition, timing, and idle speed.