SIGNAL TO NOISE RATIO EVALUATION IN SIGNAL AVERAGED ECG BY DERIVATIVE DYNAMIC TIME WARPING AND PIECEWISE LINEAR APPROXIMATION

Abstract Interpolation improves the resolution of the curve. Based on the stationary characteristics of the signal and the non-stationary characteristics of the noise, the theoretical proof indicates that the piecewise linear interpolation can improve the signal-to-noise ratio, which is further confirmed by simulation results.

Download Full-text

Nonstretching normal-moveout correction using a dynamic time warping algorithm

Geophysics ◽

10.1190/geo2016-0673.1 ◽

2018 ◽

Vol 83 (1) ◽

pp. V27-V37 ◽

Cited By ~ 8

Author(s):

Shuangquan Chen ◽

Song Jin ◽

Xiang-Yang Li ◽

Wuyang Yang

Keyword(s):

Seismic Data ◽

Dynamic Time Warping ◽

Signal To Noise Ratio ◽

Synthetic Data ◽

Optimization Method ◽

Thin Layers ◽

Time Warping ◽

Dynamic Matching ◽

Seismic Waveforms ◽

Dynamic Time

Normal-moveout (NMO) correction is one of the most important routines in seismic processing. NMO is usually implemented by a sample-by-sample procedure; unfortunately, such implementation not only decreases the frequency content but also distorts the amplitude of seismic waveforms resulting from the well-known stretch. The degree of stretch increases with increasing offset. To minimize severe stretch associated with far offset, we use a dynamic time warping (DTW) algorithm to achieve an automatic dynamic matching NMO nonstretch correction, which does not handle crossing events and convoluted events such as thin layers. Our algorithm minimizes the stretch through an automatic static temporal correction of seismic wavelets. The local static time shifts are obtained using a DTW algorithm, which is a nonlinear optimization method. To mitigate the influence of noise, we evaluated a multitrace window strategy to improve the signal-to-noise ratio of seismic data by obtaining a more precise moveout correction at far-offset traces. To illustrate the effectiveness of our algorithm, we first applied our method to synthetic data and then to field seismic data. Both tests illustrate that our algorithm minimizes the stretch associated with far offsets, and the method preserves the amplitude fidelity.

Download Full-text

MATHEMATICAL MODEL OF A CORRELATION RECEIVER WITH A PIECEWISE LINEAR APPROXIMATION OF THE DECISION FUNCTION OF THE THRESHOLD DEVICE

ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА ◽

10.36622/vstu.2021.17.4.012 ◽

2021 ◽

pp. 92-98

Author(s):

М.Ф. Волобуев ◽

В.С. Костенников ◽

А.О. Шмойлов

Keyword(s):

Mathematical Model ◽

Linear Approximation ◽

Initial Phase ◽

Signal To Noise Ratio ◽

Piecewise Linear ◽

Decision Function ◽

Piecewise Linear Approximation ◽

Threshold Device ◽

Radio Signals ◽

Correlation Receiver

Разработана математическая модель двухканального корреляционного приемника радиосигналов с кусочно-линейной аппроксимацией, решающей функции порогового устройства. Приемник рассчитан на прием наиболее часто встречающихся на практике сигналов со случайной начальной фазой в условиях белого гауссовского шума. В синтезированной математической модели применяется кусочно-линейная аппроксимация решающей функции порогового устройства. Проведен сравнительный анализ характеристик обнаружения радиосигналов со случайной начальной фазой от отношения сигнал/шум, посчитанных с использованием разработанной математической модели корреляционного приемника с кусочно-линейной решающей функциeй порогового устройства. Представлены полученные в результате математического моделирования процесса функционирования корреляционного приемника при обнаружении сигналов со случайной начальной фазой в условиях шума зависимости вероятности правильного обнаружения от отношения сигнал/шум. Показано, что результаты имитационного моделирования согласуются с теоретическими расчетами. Выявлено, что представление решающих функций пороговых устройств в классической теории обнаружения сигналов в виде идеализированных (оптимальных), которые не учитывают их нелинейность, приводят либо к увеличению вероятности ложной тревоги, либо к уменьшению вероятности правильного обнаружения, что приводит к ошибкам первого рода We developed a mathematical model of a two-channel correlation receiver of radio signals with piecewise linear approximation of the decision function of the threshold device. The receiver is designed to receive the most commonly encountered signals in practice with a random initial phase in a white Gaussian noise environment. In the synthesized mathematical model, a piecewise linear approximation of the decision function of the threshold device is used. We carried out a comparative analysis of the characteristics of detecting radio signals with a random initial phase from the signal-to-noise ratio, calculated using the developed mathematical model of a correlation receiver with a piecewise linear decision function of the threshold device and known. The paper presents the dependences of the probability of correct detection on the signal-to-noise ratio obtained as a result of mathematical modeling of the process of functioning of the correlation receiver when detecting signals with a random initial phase under noise conditions. We show that the results of simulation are consistent with theoretical calculations. We found that the representation of the decision functions of threshold devices in the classical theory of signal detection in the form of idealized (optimal) ones, which do not take into account their nonlinearity, lead either to an increase in the probability of a false alarm, or to a decrease in the probability of correct detection, which leads to errors of the first kind

Download Full-text

A Fault Diagnosis System Based on Bistable Stochastic Resonance and Dynamic Time Warping

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.693.1294 ◽

2016 ◽

Vol 693 ◽

pp. 1294-1299 ◽

Cited By ~ 1

Author(s):

Zhen Wu Liu ◽

Zhi Wu Shang ◽

Ya Feng Li ◽

Tai Yong Wang

Keyword(s):

Fault Diagnosis ◽

Stochastic Resonance ◽

Dynamic Time Warping ◽

Signal To Noise Ratio ◽

Current Signal ◽

Time Warping ◽

Resonance Theory ◽

Diagnosis System ◽

Fault Diagnosis System ◽

Dynamic Time

Stator current signal of driving motor can be easily measured. Using it in the gearbox fault diagnosis system is inexpensive and suitable for remote monitoring. According to the application of the Motor Current Signal Analysis in machinery fault detection, we present a new gearbox fault diagnosis system. In modern signal processing technology, Stochastic Resonance theory is widely used to improve SNR (signal to noise ratio). Dynamic time warping algorithm is a simple and efficient way of the pattern identified. Combine the Stochastic Resonance theory and dynamic time warping algorithm as the basic theory of fault diagnosis. To realize the development of fault diagnosis software, we use the mixed-programming of MATLAB algorithms library and VC++.

Download Full-text

Determination of the Best Emulsion for the Microscopy of Crystals

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100096886 ◽

1981 ◽

Vol 39 ◽

pp. 32-33

Author(s):

David A. Grano ◽

Kenneth H. Downing

Keyword(s):

Spatial Frequency ◽

Information Transfer ◽

Signal To Noise Ratio ◽

Experimental Situation ◽

Photographic Emulsion ◽

Modulation Transfer ◽

Signal To Noise ◽

Frequency Space ◽

Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Download Full-text

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100097703 ◽

1981 ◽

Vol 39 ◽

pp. 226-227

Author(s):

W. Kunath ◽

K. Weiss ◽

E. Zeitler

Keyword(s):

Signal To Noise Ratio ◽

Carbon Support ◽

Electronic System ◽

Optic Axis ◽

Hollow Cone ◽

Signal To Noise ◽

Bright Field ◽

Noise Ratio ◽

Single Field ◽

Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Download Full-text