• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2513-2515
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for leaming in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of Butter-Worth analog filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate Butter-Worth analog filter parameter using the genetic algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.25-31
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• 2020

In an optical system that serves as the backbone of an information transmission system, it is essential to evaluate the statistical characteristics of the signal and noise for a performance evaluation and optimization of the system. The optical receiver system improves the reception sensitivity by adopting an optical amplifier in front of the optical detector to improve the reception sensitivity, but some problems change the bandwidth of the electronic signal to the optical signal in the optical receiver due to the ASE noise added to the output of the optical detector. The problem of changing the ratio of the bandwidth of these signals varies according to the passband characteristics of the filter present at the output stage. The frequency response effect can be solved by constructing an infinite order filter, but it is almost impossible to implement it. In this paper, the Butterworth filter was implemented to evaluate the frequency response characteristics of an optical receiver system according to the filter order. The simulation results showed that the receiver sensitivity increases as the order of Butter-Worth filters increases. In addition, as a result of simulation of the change of various values, it was confirmed that the reception sensitivity increased with increasing. That is, the average photocurrent increases, and the dispersion decreases with increasing.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.15-17
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of nonlinear IIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate nonlinear IIR filter parameter using the genetic algorithm.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.502-504
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of FIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate FIR filter parameter using the genetic algorithm.

• Journal of Sensor Science and Technology
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• v.30 no.2
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• pp.88-93
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• 2021

In this paper, a folding sensor based on capacitance is proposed. The sensor was developed to sense the length and angle data for the milli-scale actuators without causing any interference to the actuating joints. For the sensing and testing the robotic joint with reducing the cost and complexity aspects of manufacturing, a simple composition was adopted. The sensor comprises a pair of copper tapes, papers, and wires. The complete sensing unit is constructed by bonding the tapes with the papers and soldering the wire to the copper parts. For accuracy, a teensy 4.0 board, which has a 12-bit ADC resolution, is employed. Furthermore, the sensed analog data is not translated into the unit of capacitance for accuracy; however, it is filtered using a low-pass filter and subsequently, a Butter-worth filter. The data obtained demonstrate a periodic waveform, which implies that the data are in good agreement with the hypothesis set prior to the experiments. Compared to other milli-scale sensors, this could be a better option for sensing the length and angle data for milliscale actuators.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.5
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• pp.37-42
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• 1983

The elliptic functions have transmission zeros on the imaginary axis and exhibit equal ripples in the stopband as well as in the passband. As a consequence they can be made optimal in the sense that the transition band is minimal. However the time domain behaviors turned out to be inferior to those of Chebyshev and Butterworth responses. This paper investigates the unit step responses and impulse responses in order to analyze the effects of various parameters such as passband attenuation, stopband frequencies M. etc., The following are the prominent features. Step responses of elliptic filters rise faster and produce larger overshoots and undershoots with higher natural frequencies. In the case of even functions, the initial values are non-zero which decreases as $\omega$s increases. Unlike Butter-worth or Chebyshev cases the impulse responses start with nonzero valses which also decrease as $\omega$s or order of the function increases. Eight figures are included to illustrate above analysis.