• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.363-375
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• 2004

In this paper, We show that the bandpass random signals of the form ∑$_{\alpha}$$\alpha$$_{\alpha}$ a Sin(2$\pi$f$_{\alpha}$t + b$_{\alpha}$) where a$_{\alpha}$ being a random number in [0,1], f$_{\alpha}$ a random integer in a given frequency band, and b$_{\alpha}$ a random number in [0, 2$\pi$], generate Gaussian white noise signals and hence they are adequate for simulating Continuous Markov processes. We apply the result to the fluctuation-dissipation formula for the Johnson noise and show that the probability distribution for the long term average of the power of the Johnson noise is a X$^2$ distribution and that the relative error of the long term average is (equation omitted) where N is the number of blocks used in the average.error of the long term average is (equation omitted) where N is the number of blocks used in the average.

• 한국초전도학회:학술대회논문집
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• 2009.07a
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• pp.9-9
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• 2009

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.9 no.1
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• pp.9-16
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• 2005

The random signals defined as sums of the single frequency sinusoidal signals with random amplitudes and random phases or equivalently sums of functions obtained by adding a Sine and a Cosine function with random amplitudes, are used in the double randomization method for the Monte Carlo solution of the turbulent systems. We show that these random signals can be used for studying the properties of the Johnson noise by proving that constant multiples of these signals with uniformly distributed frequencies in a fixed frequency band satisfy the properties of the Gaussian white noise.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.103.1-103.1
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• 2003

• 한국초전도학회:학술대회논문집
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• v.14
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• pp.2-2
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2003.10a
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• pp.201.1-201.1
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• 2003

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.103.2-103.2
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• 2003

• JSTS:Journal of Semiconductor Technology and Science
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• v.9 no.3
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• pp.125-135
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• 2009

An analytical 2-dimensional model to explain the small signal and noise properties of an AlGaN/GaN modulation doped field effect transistor has been developed. The model is based on the solution of two-dimensional Poisson's equation. The developed model explains the influence of Noise in ohmic region (Johnson noise or Thermal noise) as well as in saturated region (spontaneous generation of dipole layers in the saturated region). Small signal parameters are obtained and are used to calculate the different noise parameters. All the results have been compared with the experimental data and show an excellent agreement and the validity of our model.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.445-454
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• 2006

We describe a solution to the Ornstein-Uhlenbeck equation $\frac{dI}{dt}-\frac{1}{\tau}$I(t)=cV(t) where V(t) is a constant multiple of a Gaussian white noise. Our solution is based on a discrete set of Gaussian white noise obtained by taking sample points from a sum of single frequency harmonics that have random amplitudes, random frequencies, and random phases. Hence, it is different from the solution by the standard random walk using random numbers generated by the Box-Mueller algorithm. We prove that the power of the signal has the additive property, from which we derive that the Lyapunov characteristic exponent for our solution is positive. This compares with the solution by other methods where the noise is kept to be in an error range so that its Lyapunov exponent is negative.

• Journal of Electrical Engineering and Technology
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• v.2 no.1
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• pp.136-141
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• 2007

The Purpose Of This Paper Is To Use A Tactile Sensor To Compensate The Error Rate. Most Automated Sphygmomanometers Use The Oscillometric Method And Characteristic Ratio To Estimate Systolic And Diastolic Blood Pressure. However, Based On The Fact That Maximum Amplitude Of The Oscillometric Waveform And Characteristic Ratio Are Affected By Compliance Of The Aorta And Large Arteries, A Method To Measure The Artery Stiffness By Using A Tactile Sensor Was Chosen In Order To Integrate It With The Sphygmomanometer In The Future Instead Of Using Photoplethysmography. Since Tactile Sensors Have Very Weak Movements, Efforts Were Made To Maintain The Subject's Arm In A Fixed Position, And A 40hz Low Pass Filter Was Used To Eliminate Noise From The Power Source As Well As High Frequency Noise. An Analyzing Program Was Made To Get Time Delay Between The First And Second Peak Of The Averaged Digital Volume Pulse(${\Delta}t_{dvp}$), And The Subject's Height Was Divided By ${\Delta}t_{dvp}$ To Calculate The Stiffness Index Of The Arteries($Si_{dvp}$). Regression Equations Of Systolic And Diastolic Pressure Using $Si_{dvp}$ And Mean Arterial Pressure(Map) Were Computed From The Test Group (60 Subjects) Among A Total Of 121 Subjects(Age: $44.9{\pm}16.5$, Male: Female=40:81) And Were Tested In 61 Subjects To Compensate The Error Rate. Error Rates Considering All Subjects Were Systolic $4.62{\pm}9.39mmhg$, And Diastolic $14.40{\pm}9.62mmhg$, And Those In The Test Set Were $3.48{\pm}9.32mmhg,\;And\;14.34{\pm}9.67mmhg$ Each. Consequently, Error Rates Were Compensated Especially In Diastolic Pressure Using $Si_{dvp}$, Various Slopes From Digital Volume Pulse And Map To Systolic-$1.91{\pm}7.57mmhg$ And Diastolic $0.05{\pm}7.49mmhg$.