• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.6
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• pp.58-61
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• 1983

This is a Loudness Control Circuit in an audio amplifier controlled by feedback type volume control variable resistors. This circuit consists of Bridged Twin T network and a ordinary variable resistor. The variably resistor acts not only as a volume control by varying feedback qupntity, but also as Loudness Control through the characteristics variation by Sound Level. This new Loudness Control Circuit showed ideal compensation characteristics that agree computer simulation and measured datas.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.63-67
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• 2004

We know that Neural Network is in use in many control fields. In time of using as controller, Neural Network controller is needed to learning by Input-output pattern. But in many times of control field. we can not get Input-output pattern of Neural Network controller. As a method solving this problem, in this paper, we try New control method that output node of Neural Network bringing control object. Such a New control method application, we can solve the data taking problem to Neural Network controller Input-output. The effectiveness of proposed control algorithm is verified by simulation results of DC servo motor.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.1
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• pp.40-49
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• 2008

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications and so of due to their excellent power to weight ratio. To obtain maximum efficiency in these applications, this paper proposes the neural network control method. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the error back propagation algorithm(EBPA) of neural network. The minimization of loss is possible to realize eHciency optimization control for the IPMSM drive. This paper proposes high performance and robust control through a real time calculation of parameter variation such as variation of back emf constant, armature resistance and d-axis inductance about the motor operation. Proposed algorithm is applied IPMSM drive system, prove validity through analysis operating characteristics con011ed by efficiency optimization control.

• Journal of IKEEE
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• v.24 no.4
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• pp.975-981
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• 2020

A 10 GHz LC voltage-controlled oscillator (VCO), which controls an amplitude of output signal, is proposed to improve the phase noise. The proposed amplitude control circuit for the LC VCO consists of a peak detector, an amplifier, and a current source. The peak detector is performed detecting the lowest voltage of the output signal by using two diode-connected NMOSFET and a capacitor. The proposed 10 GHz LC VCO with an amplitude control circuit for output signal is designed using a 55 nm CMOS process with a supply voltage of 1.2 V. Its area is 0.0785 ㎟. The amplitude control circuit used in the proposed LC VCO reduces the amplitude variation 242 mV generated in the output signal of the conventional LC VCO to 47 mV. Furthermore, it improves the peak-to-peak time jitter from 8.71 ps to 931 fs.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.442-448
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• 2000

The conventional control of dynamic systems needs accurate mathematical modeling of control systems. But the modeling of dynamic systems require very complex computation process due to complex state equation and many control parameters. Accordingly this paper proposes a state space identification model of the dynamic system using neural networks. The Gauss-Newton method is used to train the proposed neural network and the effectiveness of proposed method is verified through the computer simulation of the Seesaw system identification problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.456-459
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• 2001

In this paper, a wavelet neural network for adaptive control was proposed. The structure of this network is similar to that of the multilayer perceptron(MLP), except that here the sigmoid functions are replated by mother wavelet function in the hidden units. The simulation result showed the effectiveness of using the wavelet neural network structure in the adaptive control of one-link manipulator.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.382-387
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• 1998

The adaptive hysteresis band current control method using neural network is proposed to hold the switching frequency of PWM inverter constant at any operating points of ac motor. The adaptive hysteresis band equation is derived as the teaching signal of neural network. and then the structure and learning algorithm of the neural network a are suggested. The simulation results show that the switching frequency of PWM inverter is held constant at any operating conditions of ac motor and the proposed method has good transient performance of stator current.

• 발명특허
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• v.29 no.10 s.340
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• pp.62-65
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• 2004

• Electric Engineers Magazine
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• s.152
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• pp.20-29
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• 1995

• 발명특허
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• v.30 no.5 s.347
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• pp.59-62
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• 2005