ENHANCEMENT OF SIGNAL‐TO‐NOISE RATIO IN MAGNETOTELLURIC DATA

Geophysics ◽  
1977 ◽  
Vol 42 (1) ◽  
pp. 103-110 ◽  
Author(s):  
Dominic W. Kao ◽  
David Rankin
Keyword(s):  
Confidence Limit ◽  
Signal To Noise Ratio ◽  
Data Selection ◽  
Cyclic Process ◽  
Signal To Noise ◽  
Magnetotelluric Data ◽  
Cyclic Operation ◽  
Noise Ratio ◽  
A New Technique ◽  
Incoherent Noise

A new technique has been developed which can be employed for the enhancement of the signal‐to‐noise ratio of magnetotelluric data and/or for the establishment of a confidence limit as a criterion for final data selection. This technique functions in a consecutively cyclic process which can finally remove the noise from the autopower estimates of MT data if the crosspower estimates are noise free and, consequently, the predicted coherencies can be improved. When noise exists in both autopower and crosspower estimates, the cyclic operation can establish a confidence limit which reveals a direct measure of incoherent noise content and thus is a more reliable criterion than the predicted coherency itself for data selection. The technique is tested using actual MT data and the result shows the adequacy of the technique. It selects useful data from those originally having moderate or low predicted coherencies; thus it appears to be important when the predicted coherency of the majority of the collected data is not high.

On: “Enhancement of Signal‐to‐noise Ratios in Magnetotelluric Data” by Dominic W. Kao and David Rankin (GEOPHYSICS, February 1977, p. 103–110).

Geophysics ◽  
1979 ◽  
Vol 44 (9) ◽  
pp. 1594-1596 ◽  
Author(s):  
W. Hernandez ◽  
J. Jacobs
Keyword(s):  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Magnetotelluric Data ◽  
General Validity ◽  
The Cross ◽  
Noise Ratio

In their paper, Kao and Rankin present a technique designed to enhance the signal‐to‐noise ratio of magnetotelluric (MT) data. In particular, they claim it can remove the noise from the autopower estimates of MT data if the cross‐power estimates are noise free and, hence, increase the coherency of the data. We present a hypothetical, but realistic, example which we feel raises serious questions related to the general validity of the technique.

scholarly journals The influence of geomagnetic storms on magnetotelluric data analysis

2021 ◽  
Author(s):  
Hao Chen ◽  
Hideki Mizunaga ◽  
Toshiaki Tanaka
Keyword(s):  
Geomagnetic Storm ◽  
Geomagnetic Storms ◽  
Signal To Noise Ratio ◽  
Weather Forecast ◽  
Impedance Tensor ◽  
Signal To Noise ◽  
Magnetotelluric Data ◽  
Usable Information ◽  
Continuous Noise ◽  
Noise Ratio

Abstract The geomagnetic storm is a temporary disturbance of the earth's magnetosphere caused by a solar wind shock wave interacts with the earth's magnetic field. It is rarely acquired in the practical magnetotelluric (MT) survey. The rare MT researcher pays attention to the influence of geomagnetic storms on the MT data. MT data include the natural electromagnetic signals and artificial noises (instrumental, humanmade, and so on). Therefore, not all the time series contain usable information about the electrical conductivity distribution at depth, particularly when the signal-to-noise ratio is low. However, the signal-to-noise ratio will increase when there is a geomagnetic storm. In this paper, we focus on research the influences of the geomagnetic storm on MT data. Three case studies were demonstrated to show the positive effect of the geomagnetic storm on MT data. As a result, we could obtain reliable MT impedances at the noisy site using the geomagnetic storm data. It is difficult to get a reliable impedance tensor under electromagnetic environments contaminated by continuous noise. Therefore, predicting the geomagnetic storm by the space weather forecast before acquiring the MT data is effective. Utilizing the MT data during a geomagnetic storm may get a reliable result at the site contaminated by the continuous noise.

A new power-based method to determine the first arrival information of an acoustic emission wave

2018 ◽  
Vol 18 (5-6) ◽  
pp. 1620-1632 ◽  
Author(s):  
Avik Kumar Das ◽  
Christopher KY Leung
Keyword(s):  
Acoustic Emission ◽  
Arrival Time ◽  
Signal To Noise Ratio ◽  
Source Location ◽  
Signal To Noise ◽  
Power Characteristics ◽  
Wide Range ◽  
Noise Ratio ◽  
A New Technique ◽  
Wave Arrival

Acoustic emission is a powerful experimental structural health monitoring technique for determining the location of cracks formed in a member. Pinpointing wave arrival time is essential for accurate source location. Conventional arrival detection technique’s accuracy deteriorates rapidly in low signal to noise ratio (5–40 dB) region, thus unsuitable for source location due to this inaccuracy. A new technique to pinpoint the arrival time based on the power of the wave is proposed. We have designed an adaptive filter based on the power characteristics of acoustic emission wave. After filtration of the acoustic emission wave, sliding window is employed to accurately identify the region of wave arrival based on the change in transmitted power. The results from various experimental and numerical arrival time detection experiments consistently show that the proposed methodology is stable and accurate for a wide range of signal to noise ratio values (5–100 dB). Particularly, in signal to noise ratio region (5–40 dB), the method is significantly more accurate as compared to the other methods described in the literature. The method was then employed to study the localized damage progression in a steel fiber–reinforced beam under four-point bending. The results suggest that calculated source location using the new method is consistent with that from visual inspection of the member at failure and more accurate than the localization results from existing method.

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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