• KIEE International Transactions on Electrophysics and Applications
• /
• v.2C no.5
• /
• pp.273-278
• /
• 2002

Even though the modulating signal frequency of the light is too high to detect directly, the signal can be extracted by frequency conversion at the same time as the detection by means of the non-linearity of the APD. An analysis is presented for super-high-speed optical demodulation by an APD with electronic mixing. A normalized gain is defined to evaluate the performance of the frequency conversion demodulation. The nonlinear effect of the internal capacitance was included in the small signal circuit analysis. We showed theoretically and experimentally that the normalized gain is dependent on the down converted difference frequency component. In the experiment, the down converted different frequency outputs became larger than the directly detected original signal for the applied local signal of 20㏈m.

• Structural Engineering and Mechanics
• /
• v.66 no.2
• /
• pp.185-193
• /
• 2018

In this study, low- and high-frequency structure behaviors were identified and a systematic analysis procedure was proposed using noisy GPS data from a 165-m-high tower in ${\dot{I}}stanbul$, Turkey. The raw GPS data contained long- and short-periodic position changes and noisy signals at different frequencies. To extract the significant results from this complex dataset, the general structure and components of the GPS signal were modeled and analyzed in the time and frequency domains. Uncontrolled jumps and deviations involving the signal in the time domain were pre-filtered. Then, the signal was converted to the frequency domain after applying low- and high-pass filters, and the frequency and periodic component values were calculated. The spectrum of the tower motion obtained from the filtered GPS data had dominant peaks at a low frequency of $1.15572{\times}10-4Hz$ and a high frequency of 0.16624 Hz, consistent with two equivalent GPS datasets. Then, the signal was reconstructed using inverse Fourier transform with the dominant low frequency values to obtain filtered and interpretable clean signals. With the proposed sequence, processing of noisy data collected from the GPS receivers mounted very close to the structure is effective in revealing the basic behaviors and features of buildings.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.14 no.6
• /
• pp.768-776
• /
• 2014

Using a simplified high-frequency small-signal equivalent circuit model for BSIM3 MOSFET, the fully differential two-stage folded-cascode CMOS operational amplifier is analyzed to obtain its small-signal voltage transfer function. As a result, the expressions for dc gain, five zero frequencies, five pole frequencies, unity-gain frequency, and phase margin are derived for op amp design using design equations. Then the analysis result is verified through the comparison with Spice simulations of both a high speed op amp and a low power op amp designed for the $0.13{\mu}m$ CMOS process.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.25 no.2
• /
• pp.251-254
• /
• 2014

In this paper, we studied a technique of extracting a Frequency Hopping(FH) signal for analysis using high-speed parallel processing structure. Unlike fixed frequency signal, FH signal is difficult to detect and analyze because FH systems use many random frequencies instead of a single carrier frequency. To solve this problem we designed a method that analyze FH signal using high-speed parallel processing. In order to apply parallel processing, we use CUDA using GPU and compare single processing with prarallel processing. As a result, using CUDA on a GPU is about 8.53 times faster than single processing.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.4
• /
• pp.1050-1056
• /
• 1994

When a vibration data for a rotating machine such as a pump or a compressor is concerned, the frequency fluctuation of the energy contents at an instant time may provide useful information on understanding the vibration characteristics of the rotating machinery, rather than the averaged energy distribution along the frequency axis. Especially, when a periodic signal has different spectral contents, the approach to use the averaged frequency distribution, called the normal frequency analysis, may not be appropriate to extract vibration source characteristics of the structure. This paper introduces a way to analyze the signal based on an instant time. In order to evaluate the performance of the various approach, the investigatation compares three different algorithms which are frequently implemented in the instantaneous frequency analysis. Also for the noise effect embodied in the true signal, various cases for different SN ratio have been examined. The result shows that the noise level is crucial to evalute the instantaneous frequency analysis. In order to implement the instantaneous frequency analysis, the extraction of the relevant information from the measured signal should have the high S/N ratio, i, e., 40 dB or above.

• The Transactions of the Korean Institute of Electrical Engineers C
• /
• v.49 no.11
• /
• pp.616-621
• /
• 2000

This paper deals with the multiresolution analysis of wavelet transform for partial discharge(PD). Test arrangement is based on the needle-plane electrode system and applied AC high voltage. The measured PD signal was decomposed into "approximations" and "details". The approximation are the high scale, low-frequency components of the PD signal. The details are the low-scale, high frequency components. The decomposition process are iterated to 3 level, with successive approximation being decomposed in turn, so that PD signal is broken down into many lower-resolution components. Through the procedure of signal wavelet transform, signal noise extraction and signal reconstruction, the signal is analyzed to determine the magnitude of PD.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.1183-1186
• /
• 1998

Adaptive nois canceller can extract the noiseremoved spech in noisy speech signal by adapting the filter-coefficients to the background noise environment. A kind of LMS algorithm is one of the most popular adaptive algorithm for noise cancellation due to low complexity, good numerical property and the merit of easy implementation. However there is the matter of increasing misadjustment at voiced speech signal. Therefore the demanded speech signal may be extracted. In this paper, we propose a fast and noise robust wavelet packet adaptive noise canceller with NLMS-SUM method LMS combined algorithm. That is, we decompose the frequency of noisy speech signal at the base of the proposed analysis tree structure. NLMS algorithm in low frequency band can efficiently dliminate the effect of the low frequency noise and SUM method LMS algorithm at each high frequency band can remove the high frequency nosie. The proposed wavelet packet adaptive noise canceller is enhanced the more in SNR and according to Itakura-Satio(IS) distance, it is closer to the clean speech signal than any other previous adaptive noise canceller.

• Journal of information and communication convergence engineering
• /
• v.6 no.4
• /
• pp.439-443
• /
• 2008

It is shown that even if the modulating frequency of the light is too high for direct detection the signal can be extracted by frequency conversion at the same time as the detection by means of the nonlinearity of the APD. When this frequency conversion detection is applied to an optical receiver, the detection bandwidth can be increased while the configuration of the optical detection circuit and the signal processing in the subsequent stages are simplified. A fundamental analysis is carried out with an APD which is confirmed experimentally.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.294-294
• /
• 2000

In this paper, we would like to discuss the signal processing and the algorithm for ECG analysis. The ECG gives us information about the condition of the heart muscle, because myocardial abnormality or infarction is inscribed on the ECG during myocardial depolarization and repolarization. Analyzing the ECG signal, we can find heart disease, for example, arrhythmia and myocardial infarction, etc. Particularly, detecting arrhythmia is more important, because serious arrhythmia can take away the life from patients within ten minutes. The wavelet transform decomposes the ECG signal into high and low frequency component using wavelet function. Recomposing high frequency bands including QRS complex, we can detect QRS complex and eliminate the noise from the original ECG signal. To recognize the ECG signal pattern, we adopted the curve-fitting partially and statistical method. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. Comparing the approximated ECG pattern with some kinds of heart disease ECG pattern, we can detect and classify the kind of heart disease.

• 전기의세계
• /
• v.13 no.2
• /
• pp.5-10
• /
• 1964

Some nonlinearities in feedback control systems, such as relay servo, Coulomb friction, saturating amplifier of backlash in gears cause some undesirable effects. These may be static errors, limit cycles or jump phenomena. So, linearizing method of these nonlinearities using dither signals was first suggested by Loeb. He pointed out that the addition of high frequency signal to either the input or the output of a nonlinear system would make the nonlinear performance approximate the performance of linear systems. He used high-frequency sinusoidal wave as dither signal. But, in this thesis, general method of analysis is suggested for nonlinear control systmes using various dither signals, such as noise signal of Gaussian amplitude distribution, sinusoidal dither signal and sawtooth dither signal. Also, the advantage and disadvantage of these dither signals are compared. Throughout the analysis statistical method is adopted and lastly analog computer is used for the experiment of various nonlinear systems using dither signals.