• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1289-1292
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• 1998

HCI(human computer interface) technologies have been often implemented using mouse, keyboard and joystick. Because mouse and keyboard are used only in limited situation, More natural HCI methods such as speech based method and gesture based method recently attract wide attention. In this paper, we present multi-modal input system to control Windows system for practical use of multi-media computer. Our multi-modal input system consists of three parts. First one is virtual-hand mouse part. This part is to replace mouse control with a set of gestures. Second one is Windows control system using speech recognition. Third one is Windows control system using gesture recognition. We introduce neural network and HMM methods to recognize speeches and gestures. The results of three parts interface directly to CPU and through Windows.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.62-64
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• 1996

Neural network as a controller of a nonlinear system and a system identifier has been studied during the past few years. A well trained neural network identifier can be used as a system predictor. We proposed the method to design multi-step ahead predictor and multi-step predictive controller using neural network. We used the input and out put data of B system to train the NNP and used the forecasted approximat system output from NNP as B input of NNC. In this paper we used two-step ahead predictive controller to test B heating controll system and compared with PI controller.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.373-377
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• 2023

The Monte Carlo (MC) method has become an indispensable part of the nuclear radiation research field. Several widely used and well-known MC packages were developed for simulation of radiation transport and interaction with matter. All these MC packages require users to prepare an input script. The input script can become lengthy for complex models. The process of preparing these input scripts is time-consuming and error-prone. In the present work, we have developed an open-source GUI computer program for modelling radiation transport and interaction in multi-segmented slab phantoms using grid-based system for the widely used PHITS MC package. The developed tools would be useful for future users of PHITS MC package and particularly inexperienced users. The present program is distributed under GPL license and all users can freely download, modify and redistribute the program without any restrictions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.194-198
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• 1998

A novel fuzzy basis function vector- based adaptive control approach for Multi-input and Multi-output(MIMO) system is presented in this paper, in which the nonlinear plants is first linearised, the fuzzy basis function vector is then introduced to adaptively learn the upper bound of the system uncertainty vector, and its output is used as the paramenters of the compensator in the sense that both the robustness and the asymptotic error convergence can be obtained for the closed loop nonlinear control system.

• Publications of The Korean Astronomical Society
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• v.22 no.3
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• pp.83-87
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• 2007

We designed the Intermediate Frequency(IF) distributor for multi beam backend system and manufactured Voltage to Frequency Converter(VFC) to measure the multi-beam receiver performance. Multi beam receiver has 15 channel receivers and can get 15 spectrums at once. The multi beam receiver has more observation efficiency than single beam receiver. We manufactured the 15 IF distributors to distribute IF signal for Autocorrelation spectrometer that is radio signal processor. Also, we manufactured the VF Converter to test the performance measurement of receiver for Korea VLBI Network(KVN) system which is under-construct in Seoul, Ulsan and Jeju. As a result of performance measurement, we could obtain linearity of 99.4% on the input power vs output frequency and measured the operating range of input frequency.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1041-1044
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• 1999

In This paper, we investigated the single step prediction for output responses of chaotic system with multi Input multi output using chaotic neural networks. Since the systems with chaotic characteristics are coupled between internal parameters, the chaotic neural networks is very suitable for output response prediction of chaotic system. To evaluate the performance of the proposed neural network predictor, we adopt for Lorenz attractor with chaotic responses and compare the results with recurrent neural networks. The results demonstrated superior performance on convergence and computation time than the predictor using recurrent neural networks. And we could also see good predictive capability of chaotic neural network predictor.

• Journal of Digital Contents Society
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• v.5 no.4
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• pp.264-268
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• 2004

MIMO(Multi-Input Multi-Output)) system, which can increase the channel capacity by in multiple transmit and/or receive antennas, has been intensively studied for higher data rates and better quality in wireless communications. This paper treats the MIMO channel modeling and analyze the performance of V-BLAST system with ZF receiver and MMSE reciver, using OSUS algorithm respectively, over MIMO channel.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.9 s.102
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• pp.1070-1076
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• 2005

Vibration test using the MAST(multi axial simulation table) provide a more reliable testing environment than any conventional one. The multi axial simulation could be possible with a advanced control algorithm and hardware supports so that most of the operation is automatically conducted by MAST system itself except the input information that is synthesized by the measured response signals. That means the reliability of the vibration test is highly depended on the quality of the input profile. In this paper, the optimal algorithm based on the energy method is introduced to construct a best combination of candidated input PSD data could be constructed. Since the optimal algorithm renders time information, the nitration fatigue test is completely possible for any measured signals one wants. The proposed method is explained with representing acquired road signals from the candidate input PSD obtained from a proving ground.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.10-17
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• 2006

For orthogonal frequency division multiplexing (OFDM), cyclic prefix (CP) should be longer than the length of channel impulse response, resulting in a loss of bandwidth efficiency. In this letter, the CP reconstruction (CPR) technique is first applied to a multi-input multi-output (MIMO)-OFDM system with insufficient CP. The intercarrier interference (ICI) from multiple transmit antennas is so large for MIMO system that it can not be sufficiently suppressed with the conventional CPR procedure used in single-input single-output (SISO) system. A new minimum mean-square error (MMSE) equalization and ordering process is proposed for MIMO system to suppress the ICI during the CPR procedure. By applying the proposed CPR algerian to MIMO-OFDM system, we can obtain both the benefits of multiplexing gai and spectral efficiency gain.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.2
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• pp.19-25
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• 2003

For a class of multi-input multi-output nonlinear systems which perform a given task repetitively, an extended type of a direct leaning control (DLC) is proposed using the information on the (vector) relative degree of a multi-input multi-output system. Existing DLC methods are observed to be applied to a limited class of systems with the relative degree one and a new DLC law is suggested which can be applied to systems having higher relative degree. Using the proposed control law, the control input corresponding to the new desired output trajectory is synthesized directly based on the control inputs obtained from the learning process for other output trajectories. To show the validity and the performance of the proposed DLC, simulations are performed for trajectory tracking control of a two-axis SCARA robot.