SIMILARITY OF OUTPUT TRACES AS A SEISMIC OPERATOR CRITERION

Geophysics ◽  
1955 ◽  
Vol 20 (2) ◽  
pp. 254-269 ◽  
Author(s):  
Stephen M. Simpson
Keyword(s):  
Input Signal ◽  
Input Data ◽  
Signal To Noise Ratio ◽  
Linear Operators ◽  
High Input ◽  
Signal To Noise ◽  
Numerical Work ◽  
Input And Output ◽  
Definition Of

The problem of emphasizing signals on multiple trace seismograms is approached by considering a relationship between the input and output records. It is proposed that the transformation to output record be one which causes the output traces to be most “similar” or “in phase” according to a certain definition of this property. If the noise and signal are “properly behaved,” it may be demonstrated that a linear transformation chosen by this criterion must have a response emphasizing frequency ranges of high input signal‐to‐noise ratio. The determination of such a transformation from the input data alone is carried out for discrete linear operators. The numerical work involved in computing such operators is formidable. As an example the computations were carried out for a mixture of an artificial signal introduced into a noise record. The results are about as good as those obtained with conventional filtering techniques depending on prior knowledge of input signal‐to‐noise ratios.

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.

scholarly journals Simulation of the Photodetection in the PPS CMOS Sensors

2013 ◽  
Vol 8-9 ◽  
pp. 611-618
Author(s):  
Florin Toadere ◽  
Radu Arsinte
Keyword(s):  
Image Processing ◽  
Input Data ◽  
Signal To Noise Ratio ◽  
Image Processing Algorithm ◽  
Signal To Noise ◽  
Spectral Image ◽  
Image Capture ◽  
Visible Image ◽  
Optical Part ◽  
Electrical Part

The paper contains an analysis and simulation of passive pixel based sensors. The passive pixel CMOS image acquisition sensor (PPS) is the key part of a visible image capture systems. The PPS is a complex circuit composed by an optical part and an electrical part, both analog and digital. The goal of this paper is to simulate the functionality of the photodetection process that happens in the PPS sensor. The photodetector is responsible with the conversion from photons to electrical charges and then into current. In the optical part, the sensor is analyzed by a spectral image processing algorithm which uses as input data: the lenses array transmittance, the red, green and blue filters and the quantum efficiency of the PPS. In the electrical part of simulation, the program is computing the signal to noise ratio of the sensor taking into account the photon shot, white and fixed pattern noises. Our basic analysis is based on camera equation to which we add the noises.

scholarly journals Distance scaling method for accurate prediction of slowly varying magnetic fields in satellite missions

2016 ◽  
Vol 5 (2) ◽  
pp. 281-288 ◽  
Author(s):  
Panagiotis P. Zacharias ◽  
Elpida G. Chatzineofytou ◽  
Sotirios T. Spantideas ◽  
Christos N. Capsalis
Keyword(s):  
Signal To Noise Ratio ◽  
Near Field ◽  
Magnetic Behavior ◽  
Field Measurements ◽  
High Signal ◽  
Signal To Noise ◽  
Scaling Method ◽  
Magnetic Signature ◽  
The Magnetic Field

Abstract. In the present work, the determination of the magnetic behavior of localized magnetic sources from near-field measurements is examined. The distance power law of the magnetic field fall-off is used in various cases to accurately predict the magnetic signature of an equipment under test (EUT) consisting of multiple alternating current (AC) magnetic sources. Therefore, parameters concerning the location of the observation points (magnetometers) are studied towards this scope. The results clearly show that these parameters are independent of the EUT's size and layout. Additionally, the techniques developed in the present study enable the placing of the magnetometers close to the EUT, thus achieving high signal-to-noise ratio (SNR). Finally, the proposed method is verified by real measurements, using a mobile phone as an EUT.

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 Determination of Flumequine in Channel Catfish by Liquid Chromatography with Fluorescence Detection

1999 ◽  
Vol 82 (3) ◽  
pp. 614-619 ◽  
Author(s):  
Steven M Plakas ◽  
Kathleen R El Said ◽  
F Aladar Bencsath ◽  
Steven M Musser ◽  
Calvin C Walker
Keyword(s):  
Liquid Chromatography ◽  
Fluorescence Detection ◽  
Ictalurus Punctatus ◽  
Channel Catfish ◽  
Solid Phase ◽  
Signal To Noise Ratio ◽  
Methanol Solution ◽  
Signal To Noise ◽  
Relative Standard

Abstract Rapid methods are described for determination of flumequine (FLU) residues in muscle and plasma of farm-raised channel catfish (Ictalurus punctatus). FLU residues were extracted from tissues with an acidified methanol solution, and extracts were cleaned up on C18 solid-phase extraction cartridges. FLU concentrations were determined by liquid chromatography (LC)using a C18 analytical column and fluorescence detection (excitation, 325 nm; emission, 360 nm). Mean recoveries of FLU from fortified muscle were 87–94% at 5 levels ranging from 10 to 160 ppb (5 replicates per level). FLU recoveries from fortified plasma were 92–97% at 5 levels ranging from 20 to 320 ppb. Limits of detection (signal-to-noise ratio, 3:1)for the method as described were 3 and 6 ppb for muscle and plasma, respectively. Relative standard deviations (RSDs) for recoveries were ≤12%. Live catfish were dosed with 14C-labeled or unlabeled FLU to generate incurred residues. Recoveries of 14C residues throughout extraction and cleanup were 90 and 94% for muscle and plasma, respectively. RSDs for incurred FLU at 2 levels in muscle and plasma ranged from 2 to 6%. The identity of FLU in incurred tissues was confirmed by LC/mass spectrometry.

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