Magnetoelectric Sensors With Directly Integrated Charge Sensitive Readout Circuit—Improved Field Sensitivity and Signal-to-Noise Ratio

2011 ◽  
Vol 11 (10) ◽  
pp. 2260-2265 ◽  
Author(s):  
Zhao Fang ◽  
Ninad Mokhariwale ◽  
Feng Li ◽  
Suman Datta ◽  
Q. M. Zhang
Keyword(s):  
Room Temperature ◽  
Signal To Noise Ratio ◽  
Low Noise ◽  
Magnetic Sensors ◽  
Readout Circuit ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Field Sensitivity ◽  
Piezoelectric Layers ◽  
Noise Ratio

The large magnetoelectric (ME) coupling in the ME laminates makes them attractive for ultrasensitive room temperature magnetic sensors. Here ,we investigate the field sensitivity and signal-to-noise ratio (SNR) of ME laminates, consisting of magnetostrictive and piezoelectric layers (Metglas and piezopolymer PVDF were used as the model system), which are directly integrated with a low noise readout circuit. Both the theoretical analysis and experimental results show that increasing the number of piezoelectric layers can improve the SNR, especially at low frequencies. We also introduce a figure of merit to measure the overall influence of the piezolayer properties on the SNR and show that the newly developed piezoelectric single crystals of PMN-PT and PZN-PT have the promise to achieve a very high SNR and consequently ultra-high sensitivity room temperature magnetic sensors. The results show that the ME coefficients used in early ME composites development works may not be relevant to the SNR. The results also show that enhancing the magnetostrictive coefficient, for example, by employing the flux concentration effect, can lead to enhanced SNR.

Power spectral analysis of the diaphragm electromyogram

1983 ◽  
Vol 54 (6) ◽  
pp. 1579-1584 ◽  
Author(s):  
T. K. Aldrich ◽  
J. M. Adams ◽  
N. S. Arora ◽  
D. F. Rochester
Keyword(s):  
Power Spectrum ◽  
Signal To Noise Ratio ◽  
Normal Subjects ◽  
Chronic Obstructive ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Mean Values ◽  
The Mean ◽  
Noise Ratio ◽  
Diaphragm Fatigue

We studied the power spectrum of the diaphragm electromyogram (EMG) at frequencies between 31 and 246 Hz in four young normal subjects and five patients with chronic obstructive lung disease (COPD). Diaphragm EMGs were analyzed during spontaneous breathing and maximum inspiratory efforts to determine the effect of signal-to-noise ratio on the power spectrum and if treadmill exercise to dyspnea was associated with diaphragm fatigue. We found that the centroid frequencies of the power spectra (fc) were strongly correlated (r = 0.93) with ratios of power at high frequencies to power at low frequencies (H/L) for all subjects. Of the two indices, H/L had the largest standard deviation expressed as a percentage of the mean. The mean values of both of these decreased significantly after exercise, fc from 100.2 to 97.3 and H/L from 1.07 to 0.97. Signal-to-noise ratios were higher in maximal inspiratory efforts and after exercise in normal subjects and higher in COPD patients. The signal-to-noise ratio was correlated negatively with fc and H/L, indicating that these indices of the shape of the power spectrum are influenced by signal strength and noise levels as well as muscle function. We conclude that the fc and H/L index similar qualities of the power spectrum, that they are partially determined by the signal-to-noise ratio, and that, in some cases, exercise to dyspnea is associated with apparently mild diaphragm fatigue.

Apparatus for Cold Vapor Atomic Absorption of Mercury

1966 ◽  
Vol 49 (4) ◽  
pp. 778-782
Author(s):  
Myron M Schachter
Keyword(s):  
Atomic Absorption ◽  
Vapor Phase ◽  
Room Temperature ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Cold Vapor ◽  
Cold Vapor Atomic Absorption ◽  
Noise Ratio

Abstract An assembly of optical and electronic modules has been designed to measure submicrogram quantities of mercury in the vapor phase at room temperature. The signal-to-noise ratio is greater than 100 to 1 for 10−2 microgram (5 × 10−1 nanomole) of mercury.

scholarly journals A Temporal Model of Aural Frequency Discrimination

2021 ◽  
Author(s):  
◽  
Kaye McAulay
Keyword(s):  
Signal To Noise Ratio ◽  
Discrimination Performance ◽  
Frequency Discrimination ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Human Data ◽  
Temporal Intervals ◽  
Temporal Model ◽  
Noise Ratio ◽  
Positive Axis

<p>The importance of temporal information versus place information in frequency analysis by the ear is a continuing controversy. This dissertation developes a temporal model which simulates human frequency discrimination. The model gives guantitative measures of performance for the discrimination of sinusoids in white gaussian noise. The model simulates human frequency discrimination performance as a function of frequency and signal-to-noise ratio. The model's predictions are based on the temporal intervals between the positive axis crossings of the stimulus. The histograms of these temporal intervals were used as the underlying distributions from which indices of discriminability were calculated. Human freguency discrimination data was obtained for five observers as a function of frequency and signal-to-noise ratio. The data were analysed using the method of Group-operating-characteristic (GOC) Analysis. This method of analysis statistically removes unique noise from data. The unique noise was removed by summing observers' ratings for identical stimuli. This method of analysis gave human frequency discrimination data with less unigue noise than any existing frequency data. The human data were used for evaluating the model. The GOC Analysis was also used to study the improvement in d' as a function of stimulus replications and signal-to-noise ratio. The model was a good fit to the human data at 250 Hz, for two signal-to-noise ratios. The model did not fit the data at 1000 Hz or 5000 Hz. There was some evidence of a transition occuring at 1000 Hz. This investigation supported the idea that human frequency discrimination relies on a temporal mechanism at low frequencies with a transition to some other mechanism at about lO00 Hz.</p>

scholarly journals Comparing current noise in biological and solid-state nanopores

2019 ◽  
Author(s):  
A. Fragasso ◽  
S. Schmid ◽  
C. Dekker
Keyword(s):  
Solid State ◽  
Single Molecule ◽  
Signal To Noise Ratio ◽  
Low Cost ◽  
Ionic Current ◽  
Low Noise ◽  
Signal To Noise ◽  
Experimental Conditions ◽  
High Frequencies ◽  
Noise Ratio

AbstractNanopores bear great potential as single-molecule tools for bioanalytical sensing and sequencing, due to their exceptional sensing capabilities, high-throughput, and low cost. The detection principle relies on detecting small differences in the ionic current as biomolecules traverse the nanopore. A major bottleneck for the further progress of this technology is the noise that is present in the ionic current recordings, because it limits the signal-to-noise ratio and thereby the effective time resolution of the experiment. Here, we review the main types of noise at low and high frequencies and discuss the underlying physics. Moreover, we compare biological and solid-state nanopores in terms of the signal-to-noise ratio (SNR), the important figure of merit, by measuring free translocations of a short ssDNA through a selected set of nanopores under typical experimental conditions. We find that SiNx solid-state nanopores provide the highest SNR, due to the large currents at which they can be operated and the relatively low noise at high frequencies. However, the real game-changer for many applications is a controlled slowdown of the translocation speed, which for MspA was shown to increase the SNR >160-fold. Finally, we discuss practical approaches for lowering the noise for optimal experimental performance and further development of the nanopore technology.

Low Frequency NQR using Double Contact Cross-relaxation

2000 ◽  
Vol 55 (1-2) ◽  
pp. 37-40
Author(s):  
David Stephenson ◽  
John A. S. Smith
Keyword(s):  
Ammonium Sulphate ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Cross Relaxation ◽  
Relaxation Technique ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Line Shapes ◽  
Ammonium Dichromate ◽  
Noise Ratio

A cross-relaxation technique is described which involves two spin contacts per double reso-nance cycle. The result is an improvement in signal to noise ratio particularly at low frequencies. Experimental spectra and analyses are presented: 14N in ammonium sulphate showing that the tech-nique gives essentially the same information as previous studies; 14N in ammonium dichromate determining e2Qq/h as (76±3) kHz and η = 0.84±.04; 7Li in lithium acetylacetonate for which the spectrum (corrected for Zeeman distortion) yields e2Qq/h = (152 ±5) kHz and η=.5 ±.2. Calculated spectra are presented to demonstrate the η dependence of the line shapes for 7Li.

scholarly journals Improving the Signal to Noise Ratio of QTF Preamplifiers Dedicated for QEPAS Applications

2020 ◽  
Vol 10 (12) ◽  
pp. 4105
Author(s):  
Piotr Z. Wieczorek ◽  
Tomasz Starecki ◽  
Frank K. Tittel
Keyword(s):  
Operational Amplifier ◽  
Narrow Band ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Electrical Signal ◽  
Low Noise ◽  
Detection Sensitivity ◽  
Noise Amplitude ◽  
Signal To Noise ◽  
Noise Ratio

The signal-to-noise ratio (SNR) is a major factor that limits the detection sensitivity of quartz-enhanced photoacoustic spectroscopy (QEPAS) sensors. The higher the electrical signal level compared to the noise amplitude is the lower the concentration of gases that can be detected. For this reason the preamplifier circuits used in QEPAS should be optimized for low-frequency narrow-band applications. Moreover, special care should be taken when choosing a particular operational amplifier in either a transimpedance or voltage (differential) configuration. It turns out that depending on the preamp topology different operational amplifier parameters should be carefully considered when a high SNR of the whole QEPAS system is required. In this article we analyzed the influence of the crucial parameters of low-noise operational preamplifiers used in QEPAS applications and show the resulting limitations of transimpedance and voltage configurations.

scholarly journals A Temporal Model of Aural Frequency Discrimination

2021 ◽  
Author(s):  
◽  
Kaye McAulay
Keyword(s):  
Signal To Noise Ratio ◽  
Discrimination Performance ◽  
Frequency Discrimination ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Human Data ◽  
Temporal Intervals ◽  
Temporal Model ◽  
Noise Ratio ◽  
Positive Axis

<p>The importance of temporal information versus place information in frequency analysis by the ear is a continuing controversy. This dissertation developes a temporal model which simulates human frequency discrimination. The model gives guantitative measures of performance for the discrimination of sinusoids in white gaussian noise. The model simulates human frequency discrimination performance as a function of frequency and signal-to-noise ratio. The model's predictions are based on the temporal intervals between the positive axis crossings of the stimulus. The histograms of these temporal intervals were used as the underlying distributions from which indices of discriminability were calculated. Human freguency discrimination data was obtained for five observers as a function of frequency and signal-to-noise ratio. The data were analysed using the method of Group-operating-characteristic (GOC) Analysis. This method of analysis statistically removes unique noise from data. The unique noise was removed by summing observers' ratings for identical stimuli. This method of analysis gave human frequency discrimination data with less unigue noise than any existing frequency data. The human data were used for evaluating the model. The GOC Analysis was also used to study the improvement in d' as a function of stimulus replications and signal-to-noise ratio. The model was a good fit to the human data at 250 Hz, for two signal-to-noise ratios. The model did not fit the data at 1000 Hz or 5000 Hz. There was some evidence of a transition occuring at 1000 Hz. This investigation supported the idea that human frequency discrimination relies on a temporal mechanism at low frequencies with a transition to some other mechanism at about lO00 Hz.</p>

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