New Window Function for Very Short Acquisition Times

1998 ◽  
Vol 52 (1) ◽  
pp. 139-142 ◽  
Author(s):  
Lynne R. Spencer ◽  
Daniel D. Traficante
Keyword(s):  
Time Constant ◽  
Time Domain ◽  
Signal To Noise Ratio ◽  
Resolution Enhancement ◽  
Free Resolution ◽  
Window Function ◽  
Data Sets ◽  
Signal To Noise ◽  
Minor Losses ◽  
Better Than

An apodization function, the sinc-TRAF function (S-TRAF), has been developed for application to exponentially decaying data sets where the acquisition times ( AT) is less than or equal to one time constant, T2. For heavily truncated time-domain signals, S-TRAF is able to remove sinc ripple with only minor losses in linewidth (LW) and signal-to-noise ratio (S/N). Ripple removal achieved with the application of S-TRAF rivals that observed from use of the “ultimate ripple-free resolution enhancement” function (URFRE) for AT as low as 0.3 T2*. S-TRAF maintains LW and S/N better than URFRE for all acquisition times examined.

scholarly journals New processing tools for weak and/or spatially overlapped macromolecular diffraction patterns

1999 ◽  
Vol 55 (10) ◽  
pp. 1733-1741 ◽  
Author(s):  
Dominique Bourgeois
Keyword(s):  
Signal To Noise Ratio ◽  
Data Sets ◽  
Signal To Noise ◽  
Weighting Method ◽  
Time Resolved ◽  
Accurate Evaluation ◽  
Profile Fitting ◽  
Integration Program ◽  
Diffraction Patterns ◽  
New Processing

Tools originally developed for the treatment of weak and/or spatially overlapped time-resolved Laue patterns were extended to improve the processing of difficult monochromatic data sets. The integration programPrOWallows deconvolution of spatially overlapped spots which are usually rejected by standard packages. By using dynamically adjusted profile-fitting areas, a carefully built library of reference spots and interpolation of reference profiles, this program also provides a more accurate evaluation of weak spots. In addition, by using Wilson statistics, it allows rejection of non-redundant strong outliers such as zingers, which otherwise may badly corrupt the data. A weighting method for optimizing structure-factor amplitude differences, based on Bayesian statistics and originally applied to low signal-to-noise ratio time-resolved Laue data, is also shown to significantly improve other types of subtle amplitude differences, such as anomalous differences.

MIMO Detectors: A Comprehensive Performance Analysis

2021 ◽  
Vol 16 (3) ◽  
pp. 24-27
Author(s):  
E. Obi ◽  
B.O. Sadiq ◽  
O.S . Zakariyya ◽  
A. Theresa
Keyword(s):  
Error Rate ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Signal To Noise ◽  
High Data ◽  
Noise Ratio ◽  
Better Than

Multiple-input multiple-output (MIMO) systems are increasingly becoming popular due to their ability to multiply data rates without any expansion in the bandwidth. This is critical in this era of high-data rate applications but limited bandwidth. MIMO detectors play an important role in ensuring effective communication in such systems and as such the performance of the following are compared in this paper with respect to symbol error rate (SER) versus signal-to-noise ratio (SNR): maximum likelihood (ML), zero forcing (ZF), minimum mean square error (MMSE) and vertical Bell laboratories layered space time (VBLAST). Results showed that the ML has the best performance as it has the least Symbol Error Rate (SER) for all values of Signal to Noise Ratio (SNR) as it was 91.9% better than MMSE, 99.6% better than VBLAST and 99.8% better than ZF at 20db for a 2x2 antenna configuration., it can also be deduced that the performance increased with increase in number of antenna for all detectors except the V-BLAST detector.

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 Comparison of 25 Gbps NRZ & PAM-4 Modulation Used in Reference, Legacy, & Premium Backplane Channels

2012 ◽  
Vol 2012 (1) ◽  
pp. 000283-000294 ◽  
Author(s):  
Chad Morgan ◽  
Adam Healey
Keyword(s):  
Insertion Loss ◽  
Signal To Noise Ratio ◽  
High Density ◽  
Advanced Materials ◽  
Signal To Noise ◽  
Baud Rate ◽  
Noise Ratio ◽  
Better Than

Standards bodies are now examining how to increase the throughput of high-density backplane links to 25 Gbps. One method for achieving this is to construct premium backplane links utilizing advanced materials and connectors. Another approach is to re-use legacy backplanes by employing PAM-4 signaling at half of the baud rate. For PAM-4 to offer an advantage over NRZ, the signal-to-noise ratio (SNR) at the slicer input, i.e. after equalization, must be ∼9.5 dB better than NRZ to overcome loss of separation between signal levels. This paper will examine 25 Gbaud NRZ and 12.5 Gbaud PAM-4 signaling across varying levels of channel insertion loss and crosstalk. The paper provides a reliable reference for engineers to use when considering when it is appropriate to use NRZ signaling at 25 Gbaud and when it is appropriate to use PAM-4 signaling at 12.5 Gbaud for successful high-density backplane operation.

Frequency resolution of Fourier and maximum entropy spectral estimates

Geophysics ◽  
1982 ◽  
Vol 47 (9) ◽  
pp. 1303-1307 ◽  
Author(s):  
S. L. Marple
Keyword(s):  
Maximum Entropy ◽  
Signal To Noise Ratio ◽  
Frequency Resolution ◽  
Sampled Data ◽  
Signal To Noise ◽  
Analytic Determination ◽  
Spectral Estimates ◽  
The Mean ◽  
Better Than

An analytic determination of the frequency resolution for maximum entropy and conventional Blackman‐Tukey spectral estimates is made for the case of known autocorrelation. As the signal‐to‐noise ratio decreases, the maximum entropy resolution is no better than that achievable by the Blackman‐Tukey spectral estimate. The mean resolution of an ensemble of spectra constructed from sampled data sequences agrees with the analytic result.

scholarly journals Applications of Continuous Wave Free Precession Sequences in Low-Field, Time-Domain NMR

2019 ◽  
Vol 9 (7) ◽  
pp. 1312 ◽  
Author(s):  
Tiago Bueno Moraes ◽  
Tatiana Monaretto ◽  
Luiz Colnago
Keyword(s):  
Time Domain ◽  
Continuous Wave ◽  
Signal To Noise Ratio ◽  
Flip Angle ◽  
Time Interval ◽  
Single Shot ◽  
Free Precession ◽  
Signal To Noise ◽  
Low Field ◽  
Noise Ratio

This review discusses the theory and applications of the Continuous Wave Free Precession (CWFP) sequence in low-field, time-domain nuclear magnetic resonance (TD-NMR). CWFP is a special case of the Steady State Free Precession (SSFP) regime that is obtained when a train of radiofrequency pulses, separated by a time interval Tp shorter than the effective transverse relaxation time (T2*), is applied to a sample. Unlike regular pulsed experiments, in the CWFP regime, the amplitude is not dependent on T1. Therefore, Tp should be as short as possible (limited by hardware). For Tp < 0.5 ms, thousands of scans can be performed per second, and the signal to noise ratio can be enhanced by more than one order of magnitude. The amplitude of the CWFP signal is dependent on T1/T2; therefore, it can be used in quantitative analyses for samples with a similar relaxation ratio. The time constant to reach the CWFP regime (T*) is also dependent on relaxation times and flip angle (θ). Therefore, T* has been used as a single shot experiment to measure T1 using a low flip angle (5°) or T2, using θ = 180°. For measuring T1 and T2 simultaneously in a single experiment, it is necessary to use θ = 90°, the values of T* and M0, and the magnitude of CWFP signal |Mss|. Therefore, CWFP is an important sequence for TD-NMR, being an alternative to the Carr-Purcell-Meiboom-Gill sequence, which depends only on T2. The use of CWFP for the improvement of the signal to noise ratio in quantitative and qualitative analyses and in relaxation measurements are presented and discussed.

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