Estimation of Noise Level and Signal to Noise Ratio of Laplacian Electrocardiogram During Ventricular Depolarization and Repolarization

2002 ◽  
Vol 25 (10) ◽  
pp. 1474-1487 ◽  
Author(s):  
JIE LIAN ◽  
SRIRAM SRINIVASAN ◽  
HO-CHIE TSAI ◽  
DONGSHENG WU ◽  
BOAZ AVITALL ◽  
...  
Keyword(s):  
Noise Level ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Ventricular Depolarization

A Signal-to-Noise Ratio Model for the Speech-Reception Threshold of the Hearing Impaired

1986 ◽  
Vol 29 (2) ◽  
pp. 146-154 ◽  
Author(s):  
Reinier Plomp
Keyword(s):  
Hearing Aids ◽  
Noise Level ◽  
Signal To Noise Ratio ◽  
Hearing Impaired ◽  
Noise Levels ◽  
Threshold Elevation ◽  
Signal To Noise ◽  
Speech Reception ◽  
Noise Ratio ◽  
Two Parameters

This paper reviews the results of a series of investigations inspired by a model of the speech-reception threshold (SRT) of hearing-impaired listeners. The model contains two parameters accounting for the SRT of normal-hearing listeners (SRT in quiet and signal-to-noise ratio corresponding to the threshold at high noise levels), two parameters describing the hearing loss (attenuation and threshold elevation in terms of signal-to-noise ratio), and three parameters describing the hearing aid (acoustic gain, threshold elevation expressed in signal-to-noise ratio, and equivalent internal noise level). Experimental data are reported for three different types of hearing impairment: presbycusis, hearing losses with a pathological origin, and noise-induced losses. The model gives an excellent description of the data. It demonstrates that for many hearing-impaired persons speech intelligibility at noise levels beyond 50 to 60 dB(A) is their main problem, whereas hearing aids are most effective below that noise level.

DE-NOISING AND BASELINE WANDERING REMOVAL OF ELECTROCARDIOGRAM USING DOUBLE DENSITY DISCRETE WAVELET

2007 ◽  
Vol 05 (03) ◽  
pp. 399-415 ◽  
Author(s):  
R. SHANTHA SELVA KUMARI ◽  
V. SADASIVAM
Keyword(s):  
Noise Level ◽  
Signal To Noise Ratio ◽  
Discrete Wavelet ◽  
Signal To Noise ◽  
Wavelet Approximation ◽  
Baseline Wandering ◽  
Noise Ratio ◽  
Four Levels ◽  
Approximation Coefficients ◽  
Different Levels

In this paper, an off-line double density discrete wavelet transform based de-noising and baseline wandering removal methods are proposed. Different levels decomposition is used depending upon the noise level, so as to give a better result. When the noise level is low, three levels decomposition is used. When the noise level is medium, four levels decomposition is used. When the noise level is high, five levels decomposition is used. Soft threshold technique is applied to each set of wavelet detail coefficients with different noise level. Donoho's estimator is used as a threshold for each set of wavelet detail coefficients. The results are compared with other classical filters and improvement of signal to noise ratio is discussed. Using the proposed method the output signal to noise ratio is 19.7628 dB for an input signal to noise ratio of -7.11 dB. This is much higher than other methods available in the literature. Baseline wandering removal is done by using double density discrete wavelet approximation coefficients of the whole signal. This is an unsupervised method allowing the process to be used in off-line automatic analysis of electrocardiogram. The results are more accurate than other methods with less effort.

scholarly journals Effect of noise in blending and deblending

Geophysics ◽  
2013 ◽  
Vol 78 (5) ◽  
pp. A35-A38 ◽  
Author(s):  
Guus Berkhout ◽  
Gerrit Blacquière
Keyword(s):  
Noise Level ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Interesting Consequence ◽  
Signal To Noise ◽  
Background Noise Level ◽  
Noise Ratio ◽  
Incoherent Source ◽  
Large Background

If simultaneous shooting is carried out by incoherent source arrays, being the condition of blended acquisition, the deblending process generates shot records with a very low residual interference (blending noise). We found, theoretically and numerically, that deblended shot records had a better background-related signal-to-noise ratio than shot records in unblended surveys. This improvement increased with increasing blending fold and decreasing survey time. An interesting consequence of this property is that blended surveys can be carried out under more severe noise conditions than unblended surveys. It is advisable to optimize the survey time in areas with a large background noise level or in areas with severe environmental restrictions.

scholarly journals A Comb-Based Capacitive MEMS Microphone with High Signal-to-Noise Ratio: Modeling and Noise-Level Analysis

Proceedings ◽  
2017 ◽  
Vol 1 (4) ◽  
pp. 346 ◽  
Author(s):  
Sebastian Anzinger ◽  
Johannes Manz ◽  
Alfons Dehe ◽  
Gabriele Schrag
Keyword(s):  
Noise Level ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Signal To Noise ◽  
Mems Microphone ◽  
Noise Ratio ◽  
Capacitive Mems ◽  
Level Analysis

scholarly journals ESTIMATION OF OTOACOUSTIC EMISION SIGNALS BY USING SYNCHRONEOUS AVERAGING METHOD / OTOAKUSTINĖS EMISIJOS SIGNALŲ ĮVERTINIMAS PANAUDOJANT SINCHRONINĮ VIDURKINIMĄ

2011 ◽  
Vol 3 (1) ◽  
pp. 50-54
Author(s):  
Linas Sankauskas ◽  
Andrius Petrėnas ◽  
Vaidotas Marozas
Keyword(s):  
Noise Level ◽  
Averaging Method ◽  
Signal To Noise Ratio ◽  
Otoacoustic Emission ◽  
Quality Measure ◽  
Signal Quality ◽  
Signal To Noise ◽  
Deterministic Component ◽  
Noise Ratio

The study presents the investigation results of synchro­nous averaging method and its application in estimation of impulse evoked otoacoustic emission signals (IEOAE). The method was analyzed using synthetic and real signals. Synthetic signals were modeled as the mixtures of deterministic compo­nent with noise realizations. Two types of noise were used: normal (Gaussian) and transient impulses dominated (Lapla­cian). Signal to noise ratio was used as the signal quality measure after processing. In order to account varying amplitude of deterministic component in the realizations weighted aver­aging method was investigated. Results show that the perfor­mance of synchronous averaging method is very similar in case of both types of noise Gaussian and Laplacian. Weighted aver­aging method helps to cope with varying deterministic component or noise level in case of nonhomogenous ensembles as is the case in IEOAE signal.

scholarly journals Near-Infrared Transmission Spectroscopy of Aqueous Solutions: Influence of Optical Pathlength on Signal-To-Noise Ratio

2002 ◽  
Vol 56 (12) ◽  
pp. 1600-1606 ◽  
Author(s):  
Peter Snoer Jensen ◽  
Jimmy Bak
Keyword(s):  
Aqueous Solutions ◽  
Noise Level ◽  
Near Infrared ◽  
Signal To Noise Ratio ◽  
Pure Water ◽  
Optimal Choice ◽  
Infrared Transmission ◽  
Signal To Noise ◽  
Infrared Spectrometer ◽  
Noise Ratio

The optimal choice of optical pathlength, source intensity, and detector for near-infrared transmission measurements of trace components in aqueous solutions depends on the strong absorption of water. In this study we examine under which experimental circumstances one may increase the pathlength to obtain a measurement with higher signal-to-noise ratio. The noise level of measurements at eight different pathlengths from 0.2 to 2.0 mm of pure water and of 1 g/dL aqueous glucose signals were measured using a Fourier transform near-infrared spectrometer and a variable pathlength transmission cell. The measurements demonstrate that the noise level is determined by the water transmittance. The noise levels in the spectral region from 5000 to 4000 cm−1 show that the optimal pathlength (0.4 mm) is the same for pure water and 1 g/dL aqueous glucose solutions. When detector saturation occurs it is favorable to increase the pathlength instead of attenuating the light source. The obtained results are explained by an analytical model.

Determination of the Best Emulsion for the Microscopy of Crystals

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.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

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.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

Speech Reception in the Presence of Classroom Noise

1979 ◽  
Vol 10 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Veronica Smyth
Keyword(s):  
Signal To Noise Ratio ◽  
Learning Processes ◽  
Speech Discrimination ◽  
Signal To Noise ◽  
Speech Reception ◽  
Monosyllabic Words ◽  
Noise Ratio

Three hundred children from five to 12 years of age were required to discriminate simple, familiar, monosyllabic words under two conditions: 1) quiet, and 2) in the presence of background classroom noise. Of the sample, 45.3% made errors in speech discrimination in the presence of background classroom noise. The effect was most marked in children younger than seven years six months. The results are discussed considering the signal-to-noise ratio and the possible effects of unwanted classroom noise on learning processes.

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