• Journal of Biomedical Engineering Research
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• v.23 no.6
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• pp.477-484
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• 2002

A pacemaker autosense algorithm with dual thresholds. one for noise or tachyarrhythmia detection (noise threshold, NT) and the other for intrinsic beat detection (sensing threshold. ST), was developed to improve the sensing performance in single pass VDD electrograms. unipolar electrograms, or atrial fibrillation detection. When a deflection in an electrogram exceeds the NT (defined as 50% of 57), the autosense algorithm with dual thresholds checks if the deflection also exceeds the ST. If it does, the autosense algorithm calculates the signal to noise ratio (SNR) of the deflection to the highest deflection detected by NT but lower than ST during the last cardiac cycle. If the SNR 2, the autosense algorithm declares an intrinsic beat detection and calculates the next ST based on the three most recent intrinsic peaks. If the SNR $\geq$2, the autosense algorithm checks the number of deflections detected by NT during the last cardiac cycle in order to determine if it is a noise detection or tachyarrhythmia detection. Usually the autosense algorithm tries to set the 57 at 37.5% of the average of the three intrinsic beats, although it changes the percentage according to event classifications. The autosense algorithm was tested through computer simulation of atrial electrograms from 5 patients obtained during EP study, to simulate a worst sensing situation. The result showed that the ST levels for autosense algorithm tracked the electrogram amplitudes properly, providing more noise immunity whenever necessary. Also, the autosense algorithm with dual thresholds achieved sensing performance as good as the conventional fixed sensitivity method that was optimized retrospectively.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.44-49
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• 2012

The indirect-contact ECG measurement is a newly developed method for unconstrained and nonconscious measurement in daily Life. This study is the first step to reducing the large background noise appearing in indirect-contact ECG. This study built the thermal noise model of capacitively coupled active electrode which is used in indirect-contact ECG. The results show that the level of thermal noise estimated by the thermal noise model is much the same as that of actual background noise for the capacitively coupled active electrode alone. By applying the actual electrical properties of a sample cotton cloth to the thermal noise model, the theoretical level of thermal noise in the indirect-contact ECG was estimated. The results also show that the level of op-amp's intrinsic noise is so small that it can be negligible in comparison with thermal noise of resistors. The relationship between the level of thermal noise and the resistance of the bias resistor was derived, and it is the base for the further study how to choice the optimal resistance for the bias resistor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2655-2661
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• 2009

In this paper, an accurate noise parameters for thermal noise modeling of short channel MOSFET is derived and extracted. Fukui model for calculating the noise parameters of a MOSFET is modified by considering effects of parasitic elements in short channel, and it is compared with conventional noise model equation. In addition, for obtaining the intrinsic noise sources of devices, noise parameters(minimum noise figure $F_{min}$, equivalent noise resistance $R_n$ optimized source admittance $Y_{opt}=G_{opt}+B_{opt}$) in submicron MOSFETs is extracted. With this extraction method, the intrinsic noise parameters of MOSFET without effects of probe pad and extrinsic parasitic elements from RF noise measurements can be directly obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10A
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• pp.1579-1587
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• 1999

Bias-dependent noise models of $0.2\mu\textrm{m}$ gate length P-HEMT's which are scalable with gate width are proposed. To predict S-parameters of the P-HEMT's the intrinsic parameters except for $\tau$ subtracted the offsets introduced in this paper are normalized to the gate width and then scaled. The small-signal model parameters are expressed as fitting functions of the drain current to $\textrm{I}_{dss}$ ratio and gate width. In addition, to estimate accurately noise parameters the noise temperature $\textrm{T}_{g}$ of the intrinsic resistance, the equivalent noise conductance $\textrm{G}_{ni}$ of the gate current noise source, and the equivalent noise conductance $\textrm{G}_{no}$ of the drain current noise source are adopted as the noise model parameters. The extracted values of $\textrm{T}_{g}$ are nearly independent of drain current and gate width and their average is around the ambient temperature. The extracted values of $\textrm{G}_{ni}$ are small enough to be neglected to the circuit characteristics. From the comparison of the noise model with only $\textrm{G}_{no}$ and that having $\textrm{T}_{g}$, $\textrm{G}_{ni}$ and $\textrm{G}_{no}$ to the measured data it is fund that even the former model is in good agreement with the measured noise parameters. Thus, from a practical point of view the noise model having only the drain current noise source is confirmed as a scalable bias-dependent model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.192-198
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• 2005

Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The results by EMD method whichhas used only output vibration data are almost identical to the results by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

• Journal of Korean Association for Spatial Structures
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• v.19 no.2
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• pp.101-108
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• 2019

In this paper, the characteristic of intrinsic mode function(IMF) and its orthogonalization of ensemble empirical mode decomposition(EEMD), which is often used in the analysis of the non-linear or non-stationary signal, has been studied. In the decomposition process, the orthogonal IMF of EEMD was obtained by applying the Gram-Schmidt(G-S) orthogonalization method, and was compared with the IMF of orthogonal EMD(OEMD). Two signals for comparison analysis are adopted as the analytical test function and El Centro seismic wave. These target signals were compared by calculating the index of orthogonality(IO) and the spectral energy of the IMF. As a result of the analysis, an IMF with a high IO was obtained by GSO method, and the orthogonal EEMD using white noise was decomposed into orthogonal IMF with energy closer to the original signal than conventional OEMD.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.9
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• pp.675-681
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• 2014

This paper proposes a fault diagnosis system for an induction motor. This system uses empirical mode decomposition(EMD) to extract fault signatures and multi-layer perceptron(MLP) neural network to facilitate an accurate fault diagnosis. EMD can not only decompose a signal adaptively but also provide intrinsic mode functions(IMFs) containing natural oscillatory modes of the signal. However, every IMF does not represent fault signature, an IMF selection algorithm based on harmonics and their energy of each IMF is proposed. The selected IMFs are utilized for fault classification using MLP and this system shows approximately 98 % diagnosis accuracy for the fault vibration signal of the induction motor.

• Journal of Satellite, Information and Communications
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• v.11 no.1
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• pp.26-31
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• 2016

In this paper, we proposed a scheme to mitigate noises based on the EMD scheme for heterogeneous communication systems. Noise-corrupted data can be decomposed into a finite number of IMF components. Using the EMD method, we can mitigate noise with eliminate noise-corrupted IMF components. We proposed iteration stop rule for reduce EMD computation time. Simulation results show that proposed EMD scheme based on proposed algorithm for iteration stop rule efficiently mitigates 3 types of noise and reduces its computational time.

• Journal of Magnetics
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• v.3 no.3
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• pp.82-85
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• 1998

A portable HTS RF SQUID-based system, weighing less than 20 kg has been built for susceptometry applications in weak magnetic fields, It includes a YBCO sensor for measuring the axial magnetic field component with a resolution of about $7{\times}10^{-13} T/Hz^{1/2}.$ This is determined by the intrinsic magnetic noise in the quasi-white noise region. There is a relaxation for a sudden increase in field due to magnetic flux creep in HTS. In this instance the time did not exceed 3~5 minutes.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.4
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• pp.331-341
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• 2013

In the present work, the effect of the gate-to-drain capacitance ($C_{gd}$) on the noise performance of a symmetric tied-gate $In_{0.52}Al_{0.48}As/In_{0.53}Ga_{0.47}As$ double-gate HEMT is studied using an accurate charge control based approach. An analytical expression for the gate-to-drain capacitance is obtained. In terms of the intrinsic noise sources and the admittance parameters ($Y_{11}$ and $Y_{21}$ which are obtained incorporating the effect of $C_{gd}$), the various noise performance parameters including the Minimum noise figure and the Minimum Noise Temperature are evaluated. The inclusion of gate-to-drain capacitance is observed to cause significant reduction in the Minimum Noise figure and Minimum Noise Temperature especially at low values of drain voltage, thereby, predicting better noise performance for the device.