A comparison of data from airborne, semi‐airborne, and ground electromagnetic systems

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1379-1385 ◽  
Author(s):  
Richard S. Smith ◽  
A. Peter Annan ◽  
Patrick D. McGowan
Keyword(s):  
Signal To Noise Ratio ◽  
Digital Processing ◽  
Test Site ◽  
Massive Sulfide ◽  
Late Time ◽  
Signal To Noise ◽  
Waveform Data ◽  
Ground Survey ◽  
Ground System ◽  
Noise Ratio

The region around a small conductive massive sulfide body near Sudbury, Ontario, Canada, was used as a test site to compare airborne and ground electromagnetic (EM) systems with a new experimental EM system that uses a ground‐based transmitter and an airborne receiver. In this test survey, the semi‐airborne data were acquired with the transmitter loop used for the ground survey and the receiver normally used for the airborne system. At the time the data were acquired, there was no synchronization between the semi‐airborne receiver and the ground transmitter. However, subsequent digital processing of the full waveform data allowed the zero‐time position to be defined. The data could then be stacked and windowed. The ratio of the peak signal to the late‐time noise level for the airborne data is about 25:1, the semi‐airborne data shows signal‐to‐noise ratios of 500:1, while the signal‐to‐noise ratio for the ground data has a ratio of 50 000:1. This particular conductor is very close to the ground transmitter and receiver, so the signal‐to‐noise ratio for the ground system is very high. Numerical modeling shows that the marked advantage of the ground system is reduced when the conductor is deeper. However, the semi‐airborne system will generally show signal‐to‐noise intermediate between the airborne and ground systems. From an operational perspective, the semi‐airborne system has features of both the ground and airborne systems. Like the ground system, it is necessary to lay a transmitter loop on the ground; but because an aircraft is used, the semi‐airborne receiver can cover the survey area much more quickly.

Signal-to-noise ratio–based quality assessment method for ICESat/GLAS waveform data

2014 ◽  
Vol 53 (10) ◽  
pp. 103104 ◽  
Author(s):  
Sheng Nie ◽  
Cheng Wang ◽  
Guicai Li ◽  
Feifei Pan ◽  
Xiaohuan Xi ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Signal To Noise Ratio ◽  
Assessment Method ◽  
Signal To Noise ◽  
Waveform Data ◽  
Quality Assessment Method ◽  
Noise Ratio

Improvement of array seismic recordings by digital processing

1964 ◽  
Vol 54 (1) ◽  
pp. 277-294
Author(s):  
Alan Ryall
Keyword(s):  
Seismic Waves ◽  
Signal To Noise Ratio ◽  
Onset Time ◽  
Digital Processing ◽  
Apparent Velocity ◽  
Signal To Noise ◽  
Nuclear Explosions ◽  
Noise Ratio ◽  
The Uk ◽  
Velocity Filtering

abstract This paper contains a brief review of the operations that are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these methods (the UK method and multiple correlation). Analyses by the several techniques were made on array recordings that were obtained by the U. S. Geological Survey of seismic waves from chemical and nuclear explosions in the western United States. Seismograms were synthesized, using recordings of seismic noise and a Pn signal, such that the signal-to-noise ratio, onset time and apparent velocity of the signal were predetermined for the synthetic records. These records were then analyzed by summation, cross-multiplication and the UK method, and the results were compared. From the examples presented, it appears that for recordings with initial peak-signal-to-rms-noise ratio less than about 0.8, the best improvement can be obtained by the process of velocity filtering and summation of all the traces. For a six-element array improvement can be obtained by this method on records which have an original signal-to-noise ratio of 0.4 or greater. When the initial signal-to-noise ratio is greater than 0.8, multiplicative compounding yields about the same improvement as a process involving additive compounding and subsequent raising of the summation trace to large powers.

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.

Quantifying the Effects of Background Speech Babble on Preschool Children's Novel Word Learning in a Multisession Paradigm: A Preliminary Study

2020 ◽  
Vol 63 (1) ◽  
pp. 345-356
Author(s):  
Meital Avivi-Reich ◽  
Megan Y. Roberts ◽  
Tina M. Grieco-Calub
Keyword(s):  
Word Learning ◽  
Signal To Noise Ratio ◽  
Preschool Age ◽  
Exposure Condition ◽  
Signal To Noise ◽  
Verbal Recall ◽  
Referent Selection ◽  
Main Effect ◽  
Noise Ratio ◽  
Novel Word Learning

Purpose This study tested the effects of background speech babble on novel word learning in preschool children with a multisession paradigm. Method Eight 3-year-old children were exposed to a total of 8 novel word–object pairs across 2 story books presented digitally. Each story contained 4 novel consonant–vowel–consonant nonwords. Children were exposed to both stories, one in quiet and one in the presence of 4-talker babble presented at 0-dB signal-to-noise ratio. After each story, children's learning was tested with a referent selection task and a verbal recall (naming) task. Children were exposed to and tested on the novel word–object pairs on 5 separate days within a 2-week span. Results A significant main effect of session was found for both referent selection and verbal recall. There was also a significant main effect of exposure condition on referent selection performance, with more referents correctly selected for word–object pairs that were presented in quiet compared to pairs presented in speech babble. Finally, children's verbal recall of novel words was statistically better than baseline performance (i.e., 0%) on Sessions 3–5 for words exposed in quiet, but only on Session 5 for words exposed in speech babble. Conclusions These findings suggest that background speech babble at 0-dB signal-to-noise ratio disrupts novel word learning in preschool-age children. As a result, children may need more time and more exposures of a novel word before they can recognize or verbally recall it.

On the Signal-to-Noise Ratio for Boolean Functions

2020 ◽  
Vol E103.A (12) ◽  
pp. 1659-1665
Author(s):  
Yu ZHOU ◽  
Wei ZHAO ◽  
Zhixiong CHEN ◽  
Weiqiong WANG ◽  
Xiaoni DU
Keyword(s):  
Boolean Functions ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio
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