An experimental study of signal‐to‐noise ratio losses due to OR‐ing

1983 ◽  
Vol 74 (5) ◽  
pp. 1418-1421 ◽  
Author(s):  
William A. Struzinski ◽  
Jerrold C. Bloom
Keyword(s):  
Experimental Study ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Erratum: Experimental study of the signal-to-noise ratio of stochastic resonance systems

1993 ◽  
Vol 48 (6) ◽  
pp. 4862-4862 ◽  
Author(s):  
Gong De-chun ◽  
Hu Gang ◽  
Wen Xiao-dong ◽  
Yang Chun-yan ◽  
Qin Guang-rong ◽  
...  
Keyword(s):  
Experimental Study ◽  
Stochastic Resonance ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio

Experimental study of the signal-to-noise ratio of stochastic resonance systems

1992 ◽  
Vol 46 (6) ◽  
pp. 3243-3249 ◽  
Author(s):  
Gong De-chun ◽  
Hu Gang ◽  
Wen Xiao-dong ◽  
Yang Chun-yan ◽  
Qin Guang-rong ◽  
...  
Keyword(s):  
Experimental Study ◽  
Stochastic Resonance ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Experimental study on increasing signal-to-noise ratio of a beat note by cascading an Yb-doped fiber in an Er-fiber comb

2017 ◽  
Vol 66 (2) ◽  
pp. 024206
Author(s):  
Liu Huan ◽  
Cao Shi-Ying ◽  
Yu Yang ◽  
Lin Bai-Ke ◽  
Fang Zhan-Jun
Keyword(s):  
Experimental Study ◽  
Signal To Noise Ratio ◽  
Beat Note ◽  
Signal To Noise ◽  
Noise Ratio

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 :

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