scholarly journals i-RheoFT: Fourier transforming sampled functions without artefacts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Matthew G. Smith ◽  
Graham M. Gibson ◽  
Manlio Tassieri
Keyword(s):  
Initial Data ◽  
Spline Function ◽  
Time Window ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Signal To Noise ◽  
Access Code ◽  
Finite Set ◽  
Data Points ◽  
The Fourier Transform

AbstractIn this article we present a new open-access code named “i-RheoFT” that implements the analytical method first introduced in [PRE, 80, 012501 (2009)] and then enhanced in [New J Phys 14, 115032 (2012)], which allows to evaluate the Fourier transform of any generic time-dependent function that vanishes for negative times, sampled at a finite set of data points that extend over a finite range, and need not be equally spaced. I-RheoFT has been employed here to investigate three important experimental factors: (i) the ‘density of initial experimental points’ describing the sampled function, (ii) the interpolation function used to perform the “virtual oversampling” procedure introduced in [New J Phys 14, 115032 (2012)], and (iii) the detrimental effect of noises on the expected outcomes. We demonstrate that, at relatively high signal-to-noise ratios and density of initial experimental points, all three built-in MATLAB interpolation functions employed in this work (i.e., Spline, Makima and PCHIP) perform well in recovering the information embedded within the original sampled function; with the Spline function performing best. Whereas, by reducing either the number of initial data points or the signal-to-noise ratio, there exists a threshold below which all three functions perform poorly; with the worst performance given by the Spline function in both the cases and the least worst by the PCHIP function at low density of initial data points and by the Makima function at relatively low signal-to-noise ratios. We envisage that i-RheoFT will be of particular interest and use to all those studies where sampled or time-averaged functions, often defined by a discrete set of data points within a finite time-window, are exploited to gain new insights on the systems’ dynamics.

Assisted traveltime picking of crosshole GPR data

Geophysics ◽  
2009 ◽  
Vol 74 (4) ◽  
pp. J35-J48 ◽  
Author(s):  
Bernard Giroux ◽  
Abderrezak Bouchedda ◽  
Michel Chouteau
Keyword(s):  
Time Window ◽  
Signal To Noise Ratio ◽  
Real Data ◽  
Information Criterion ◽  
High Signal ◽  
Data Sets ◽  
Signal To Noise ◽  
Arrival Times ◽  
Common Time ◽  
Waveform Similarity

We introduce two new traveltime picking schemes developed specifically for crosshole ground-penetrating radar (GPR) applications. The main objective is to automate, at least partially, the traveltime picking procedure and to provide first-arrival times that are closer in quality to those of manual picking approaches. The first scheme is an adaptation of a method based on cross-correlation of radar traces collated in gathers according to their associated transmitter-receiver angle. A detector is added to isolate the first cycle of the radar wave and to suppress secon-dary arrivals that might be mistaken for first arrivals. To improve the accuracy of the arrival times obtained from the crosscorrelation lags, a time-rescaling scheme is implemented to resize the radar wavelets to a common time-window length. The second method is based on the Akaike information criterion(AIC) and continuous wavelet transform (CWT). It is not tied to the restrictive criterion of waveform similarity that underlies crosscorrelation approaches, which is not guaranteed for traces sorted in common ray-angle gathers. It has the advantage of being automated fully. Performances of the new algorithms are tested with synthetic and real data. In all tests, the approach that adds first-cycle isolation to the original crosscorrelation scheme improves the results. In contrast, the time-rescaling approach brings limited benefits, except when strong dispersion is present in the data. In addition, the performance of crosscorrelation picking schemes degrades for data sets with disparate waveforms despite the high signal-to-noise ratio of the data. In general, the AIC-CWT approach is more versatile and performs well on all data sets. Only with data showing low signal-to-noise ratios is the AIC-CWT superseded by the modified crosscorrelation picker.

A compact guided-wave EMAT with pulsed electromagnet for ferromagnetic tube inspection

2020 ◽  
Vol 64 (1-4) ◽  
pp. 951-958
Author(s):  
Tianhao Liu ◽  
Yu Jin ◽  
Cuixiang Pei ◽  
Jie Han ◽  
Zhenmao Chen
Keyword(s):  
Power Plants ◽  
Signal To Noise Ratio ◽  
Small Diameter ◽  
Performance Testing ◽  
Guided Wave ◽  
High Signal ◽  
Receiver Coil ◽  
Signal To Noise ◽  
Corrosion Defects

Small-diameter tubes that are widely used in petroleum industries and power plants experience corrosion during long-term services. In this paper, a compact inserted guided-wave EMAT with a pulsed electromagnet is proposed for small-diameter tube inspection. The proposed transducer is noncontact, compact with high signal-to-noise ratio and unattractive to ferromagnetic tubes. The proposed EMAT is designed with coils-only configuration, which consists of a pulsed electromagnet and a meander pulser/receiver coil. Both the numerical simulation and experimental results validate its feasibility on generating and receiving L(0,2) mode guided wave. The parameters for driving the proposed EMAT are optimized by performance testing. Finally, feasibility on quantification evaluation for corrosion defects was verified by experiments.

Narrow-frequency sharp-angular filters using all-dielectric cascaded meta-gratings

Nanophotonics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 3443-3450 ◽  
Author(s):  
Wei-Nan Liu ◽  
Rui Chen ◽  
Wei-Yi Shi ◽  
Ke-Bo Zeng ◽  
Fu-Li Zhao ◽  
...  
Keyword(s):  
Thin Film ◽  
Signal To Noise Ratio ◽  
Incident Angle ◽  
Design Strategy ◽  
Transmission Peak ◽  
High Signal ◽  
Waveguide Array ◽  
Signal To Noise ◽  
Center Wavelength ◽  
Noise Ratio

AbstractSelective transmission or filtering always responds to either frequency or incident angle, so as hardly to maximize signal-to-noise ratio in communication, detection and sensing. Here, we propose compact meta-filters of narrow-frequency sharp-angular transmission peak along with broad omnidirectional reflection sidebands, in all-dielectric cascaded subwavelength meta-gratings. The inherent collective resonance of waveguide-array modes and thin film approximation of meta-grating are employed as the design strategy. A unity transmission peak, locating at the incident angle of 44.4° and the center wavelength of 1550 nm, is demonstrated in a silicon meta-filter consisting of two-layer silicon rectangular meta-grating. These findings provide possibilities in cascaded meta-gratings spectroscopic design and alternative utilities for high signal-to-noise ratio applications in focus-free spatial filtering and anti-noise systems in telecommunications.

scholarly journals Low-dose, phase-contrast mammography with high signal-to-noise ratio

2016 ◽  
Vol 7 (2) ◽  
pp. 381 ◽  
Author(s):  
Lukas B. Gromann ◽  
Dirk Bequé ◽  
Kai Scherer ◽  
Konstantin Willer ◽  
Lorenz Birnbacher ◽  
...  
Keyword(s):  
Phase Contrast ◽  
Low Dose ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Signal To Noise ◽  
Noise Ratio

Research on LIFT Technology for 3D Seismic Denoising in Coalfield

2014 ◽  
Vol 556-562 ◽  
pp. 6328-6331
Author(s):  
Su Zhen Shi ◽  
Yi Chen Zhao ◽  
Li Biao Yang ◽  
Yao Tang ◽  
Juan Li
Keyword(s):  
Signal To Noise Ratio ◽  
High Signal ◽  
3D Seismic ◽  
Signal To Noise ◽  
Denoising Method ◽  
Seismic Processing ◽  
Work Area ◽  
Noise Data ◽  
Noise Ratio ◽  
Effective Signal

The LIFT technology has applied in process of denoising to ensure the imaging precision of minor faults and structure in 3D coalfield seismic processing. The paper focused on the denoising process in two study areas where the LIFT technology is used. The separation of signal and noise is done firstly. Then denoising would be done in the noise data. The Data of weak effective signal that is from the noise data could be blended with the original effective signal to reconstruct the denoising data, so the result which has high signal-to-noise ratio and preserved amplitude is acquired. Thus the fact shows that LIFT is an effective denoising method for 3D seismic in coalfield and could be used widely in other work area.

Head Instability Detection for Testing Process in Perpendicular Magnetic Recording System

2013 ◽  
Vol 770 ◽  
pp. 319-322 ◽  
Author(s):  
Piya Kovintavewat ◽  
Santi Koonkarnkhai ◽  
Aimamorn Suvichakorn
Keyword(s):  
Magnetic Recording ◽  
Signal To Noise Ratio ◽  
Disk Drive ◽  
Detection Algorithm ◽  
Recording System ◽  
High Signal ◽  
Signal To Noise ◽  
Perpendicular Magnetic Recording ◽  
Read Head ◽  
Pass Through

During hard disk drive (HDD) testing process, the magneto-resistive read (MR) head is analyzed and checked if the head is defective or not. Baseline popping (BLP) is one of the crucial problems caused by head instability, whose effect can distort the readback signal to the extent of causing possible sector read failure. Without BLP detection algorithm, the defective read head might pass through HDD assembling process, thus producing an unreliable HDD. This situation must be prevented so as to retain customer satisfaction. This paper proposes a simple (but efficient) BLP detection algorithm for perpendicular magnetic recording systems. Results show that the proposed algorithm outperforms the conventional one in terms of both the percentage of detection and the percentage of false alarm, when operating at high signal-to-noise ratio.

High signal-to-noise ratio quantum well bolometer materials

2006 ◽  
Author(s):  
Stanley Wissmar ◽  
Linda Höglund ◽  
Jan Andersson ◽  
Christian Vieider ◽  
Susan Savage ◽  
...  
Keyword(s):  
Quantum Well ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Signal To Noise ◽  
Noise Ratio

Bias in estimates of mb at small magnitudes

1976 ◽  
Vol 66 (6) ◽  
pp. 1887-1904
Author(s):  
J. F. Evernden ◽  
W. M. Kohler
Keyword(s):  
Signal To Noise Ratio ◽  
High Signal ◽  
Systematic Bias ◽  
Station Correction ◽  
Signal To Noise ◽  
Identification Criterion ◽  
The Difference ◽  
Operational Networks ◽  
Worldwide Network ◽  
Simple Parameter

abstract A possibly significant factor in application of an identification criterion such as MS:mb is systematic bias in mb magnitude estimates at small magnitudes due to a variety of factors. Magnitude bias is the difference in magnitude value, positive or negative, between an observed network-based magnitude value and the expected magnitude value if all stations of the network had detected the event at high signal-to-noise ratio. This paper constitutes a partial study of the general problem; it evaluates the bias effects expected from both conceptual and operational networks when using parameters for noise and signal levels and standard deviations derived from observations, and when correcting observed station mb values solely via a simple parameter station correction factor. The analysis shows that any bias effects on mb inherent in any operational or potential worldwide network are so small as to have negligible effect on use of an MS:mb discriminant.

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