Definition of Signal-to-Noise Ratio of Health Indicators and Its Analytic Optimization for Machine Performance Degradation Assessment

2021 ◽  
pp. 1-1
Author(s):  
Tongtong Yan ◽  
Dong Wang ◽  
Jin-zhen Kong ◽  
Tangbin Xia ◽  
Zhike Peng ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Health Indicators ◽  
Performance Degradation ◽  
Signal To Noise ◽  
Machine Performance ◽  
Noise Ratio ◽  
Definition Of

scholarly journals The Multi-resolution CLEAN

1991 ◽  
Vol 131 ◽  
pp. 268-271 ◽  
Author(s):  
B.P. Wakker ◽  
U.J. Schwarz
Keyword(s):  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Extended Sources ◽  
Noise Ratio ◽  
Definition Of

AbstractWe describe a modification to CLEAN which alleviates some problems for extended sources. This is accomplished by combining the results of a number of conventional CLEAN operations, each done at a different resolution. The algorithm is called “Multi-Resolution Clean” or “MRC”. Experiments on model sources have shown that it works well even when the source is so extended that the usual CLEAN becomes impractical. For extended sources, MRC enhances the signal-to-noise ratio, resulting in an easier definition of the area of signal. Moreover, MRC is in principle faster than a standard CLEAN because less δ-functions are needed. This work was published in Astr. Ap., 200, 312.

scholarly journals Definition of signal-to-noise ratio and its critical role in split-beam measurements

2005 ◽  
Vol 62 (1) ◽  
pp. 123-130 ◽  
Author(s):  
Robert Kieser ◽  
Pall Reynisson ◽  
Timothy J. Mulligan
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Role ◽  
Target Strength ◽  
Acoustic Measurements ◽  
Signal To Noise ◽  
Low Snr ◽  
Wide Range ◽  
Noise Ratio ◽  
New Equation ◽  
Definition Of

Abstract The signal-to-noise ratio (SNR) plays a critical role in any measurement but is particularly important in fisheries acoustics where both signal and noise can change by orders of magnitude and may have large variations. “Textbook situations” exist where the SNR is clearly defined, but fisheries-acoustic measurements are generally not in this category as signal and noise come from a wide range of sources that change with location, depth, and ocean conditions. This paper defines the SNR and outlines its measurement using split-beam data. Its effect on target-strength (TS) measurements is explored. Recommendations are given for the routine use of the SNR in fisheries-acoustic measurements. This work also suggests a new equation for TS estimation that is important at low SNR.

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.

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