Quantitative Spectral Evaluation of Shimmer and Jitter

1985 ◽  
Vol 28 (2) ◽  
pp. 169-174 ◽  
Author(s):  
Fritz Klingholz ◽  
Frank Martin
Keyword(s):  
Vocal Fold ◽  
Signal To Noise Ratio ◽  
Voice Disorders ◽  
Voice Disorder ◽  
Wave Spectra ◽  
Noise Levels ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Synthesized Speech ◽  
Spectral Evaluation

A vowel [a]-like, synthesized speech wave was perturbated by defined and comparable jitter and shimmer levels. The signal-to-noise ratio was calculated from the speech wave spectra. Noise emerges in those spectral regions in which the harmonics have high amplitudes, that is, at low frequencies and in the formant regions. Jitter created noise levels significantly higher than shimmer. To verify the theoretical findings, the voices of 32 women with functional voice disorders were analyzed for shimmer and jitter. It was found that only jitter is relevant for differentiating between hypo- and hyperfunctional voice disorders. Jitter was reduced in hyperfunctional voice disorder. This is presumed to be an effect of the high vocal fold tension found in the disorder.

Does Motion Perception Follow Weber's Law?

Perception ◽  
1995 ◽  
Vol 24 (4) ◽  
pp. 363-372 ◽  
Author(s):  
Johannes M Zanker
Keyword(s):  
Motion Perception ◽  
Stimulus Intensity ◽  
Signal To Noise Ratio ◽  
Weber’S Law ◽  
Noise Levels ◽  
Signal To Noise ◽  
Weber's Law ◽  
The Absolute ◽  
Noise Ratio ◽  
Random Dot Patterns

The subjective strength of a percept often depends on the stimulus intensity in a nonlinear way. Such coding is often reflected by the observation that the just-noticeable difference between two stimulus intensities (JND) is proportional to the absolute stimulus intensity. This behaviour, which is usually referred to as Weber's Law, can be interpreted as a compressive nonlinearity extending the operating range of a sensory system. When the noise superimposed on a motion stimulus is increased along a logarithmic scale (in order to provide linear steps in subjective difference) in motion-coherency measurements, observers often report that the subjective differences between the various noise levels increase together with the absolute level. This observation could indicate a deviation from Weber's Law for variation of motion strength as obtained by changing the signal-to-noise ratio in random-dot kinematograms. Thus JNDs were measured for the superposition of uncorrelated random-dot patterns on static random-dot patterns and three types of motion stimuli realised as random-dot kinematograms, namely large-field and object ‘Fourier’ motion (all or a group of dots move coherently), ‘drift-balanced’ motion (a travelling region of static dots), and paradoxical ‘theta’ motion (the dots on the surface of an object move in opposite direction to the object itself). For all classes of stimuli, the JNDs when expressed as differences in signal-to-noise ratio turned out to increase with the signal-to-noise ratio, whereas the JNDs given as percentage of superimposed noise appear to be similar for all tested noise levels. Thus motion perception is in accordance with Weber's Law when the signal-to-noise ratio is regarded as stimulus intensity, which in turn appears to be coded in a nonlinear fashion. In general the Weber fractions are very large, indicating a poor differential sensitivity in signal-to-noise measurements.

Videostrobolaryngoscopy of Mucus Layer during Vocal Fold Vibration in Patients with Laryngeal Tension-Fatigue Syndrome

2002 ◽  
Vol 111 (6) ◽  
pp. 537-541 ◽  
Author(s):  
Tzu-Yu Hsiao ◽  
Chia-Ming Liu ◽  
Kai-Nan Lin
Keyword(s):  
Mechanical Properties ◽  
Vocal Fold ◽  
Rough Surfaces ◽  
Voice Disorders ◽  
Vocal Folds ◽  
Voice Disorder ◽  
Mucus Layer ◽  
Vocal Fold Vibration ◽  
Fatigue Syndrome ◽  
Functional Dysphonia

The mucus layer on the vocal folds was examined by videostrobolaryngoscopy in patients with laryngeal tension-fatigue syndrome, a chronic functional dysphonia due to vocal abuse and misuse. Besides the findings in previous reports (such as abnormal glottal closure, phase or amplitude asymmetry, and the irregular mucosal wave), the vocal folds during vibration had an uneven mucus surface. The occurrence of an uneven mucus layer on vocal folds was significantly greater in subjects with this voice disorder (83% or 250 of 301 patients in this series) than in those without voice disorders (18.5% or 5 of 27). The increase of mucus viscosity, mucus aggregation, and the formation of rough surfaces on the vocal folds alter the mechanical properties that contribute to vibration of the cover of the vocal folds, and thereby worsen the symptoms of dysphonia in patients with laryngeal tension-fatigue syndrome.

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.

SOME TECHNICAL ASPECTS OF REFLECTION SEISMIC PROSPECTING IN THE SAHARA

Geophysics ◽  
1958 ◽  
Vol 23 (3) ◽  
pp. 557-573 ◽  
Author(s):  
M. Pieuchot ◽  
H. Richard
Keyword(s):  
Seismic Reflection ◽  
Signal To Noise Ratio ◽  
Small Signal ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Technical Aspects ◽  
Reflection Seismic ◽  
Linear Dimensions ◽  
Single Trace ◽  
Selection Of

The small signal‐to‐noise ratio encountered in the Sahara required the development of special techniques. The gentle dips and low frequencies permitted the use of a pattern of 100 shot holes recorded by an array of 100 or more geophones per trace with the linear dimensions of the arrays of the order of 100 m. The large structural dimensions allowed the compositing of as many as 5 records into a single trace. Seismic reflection exploration was made economically feasible by the use of pneumatic hammers for drilling and the less expensive nitrates for explosives. The experimental procedures leading to the selection of the techniques are described.

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.

Application of frequency-dependent multichannel Wiener filters to detect events in 2D three-component seismometer arrays

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. V133-V141 ◽  
Author(s):  
J. Wang ◽  
F. Tilmann ◽  
R. S. White ◽  
P. Bordoni
Keyword(s):  
Least Squares Method ◽  
Signal To Noise Ratio ◽  
Noise Levels ◽  
Signal To Noise ◽  
Coherent Noise ◽  
Gas Field ◽  
Frequency Dependent ◽  
Wiener Filters ◽  
Noise Ratio

Hydraulic fracture-induced microseismic events in producing oil and gas fields are usually small, and noise levels are high at the surface as a result of the heavy equipment in use. Similarly, in nonhydrocarbon settings, arrays for detecting local earthquakes will benefit from reduced noise levels and the ability to detect smaller events will be increased. We propose a frequency-dependent multichannel Wiener filtering technique with linear constraints that uses an adaptive least-squares method to remove coherent noise in seismic array data. The noise records on several reference channels are used to predict the noise on a primary channel and then can be subtracted from the observed data. On a test with an unconstrained version of this filter, maximal noise suppression leads to signal distortion. Two methods of im-posing constraints then achieve signal preservation. In one case study, synthetic signals are added to noise from a pilot deployment of a hexagonal array (nine three-component seismometers, approximately [Formula: see text]) above a gas field; noise levels are suppressed by up to [Formula: see text] (at [Formula: see text]). In a second case study, natural seismicity recorded at a dense array ([Formula: see text] spacing) in Italy is used, where the application of the filter improves the signal-to-noise ratio (S/N) more than [Formula: see text] (at [Formula: see text]) using 35 stations. In both cases, the performance of the multichannel Wiener filters is significantly better than stacking, espe-cially at lower frequencies where stacking does not help to suppress the coherent noise. The unconstrained version of the filter yields the best improvement in signal-to-noise ratio, but the constrained filter is useful when waveform distortion is unacceptable.

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 On the application of frequency tagging

2020 ◽  
Author(s):  
Zoltan Derzsi
Keyword(s):  
Phase Noise ◽  
Detection Probability ◽  
Signal To Noise Ratio ◽  
Lower Probability ◽  
Weak Signal ◽  
Signal To Noise ◽  
Noise Component ◽  
Spectral Evaluation ◽  
Human Electrophysiology ◽  
Additional Phase

To detect a weak signal in human electrophysiology that is a response of a periodic external stimulus, spectral evaluation is mostly used. The recorded signal’s amplitude and phase noise components of the signal are statistically independent from each other, but both of them are decreasing the signal-to-noise ratio, which results in a lower probability of successful signal detection. Provided that the phase information of the stimuli is preserved, we found that a way to reject an additional phase noise component, which improves the detection probability considerably, by analysing the signal’s phase coherency instead of its spectrum.

scholarly journals Performance Evaluation of Frame based Adaptive Compressed Sensing and Non-Adaptive Compressed Sensing based on Average Frame Signal to Noise Ratio

2018 ◽  
Vol 7 (4.10) ◽  
pp. 202
Author(s):  
T. S. Arulananth ◽  
R. Satheesh ◽  
P. Bhaskara Reddy
Keyword(s):  
Performance Evaluation ◽  
Compressed Sensing ◽  
Signal To Noise Ratio ◽  
Projection Matrix ◽  
Noise Levels ◽  
Signal To Noise ◽  
Normal Frame ◽  
Noise Ratio

The primary inspiration of our work is to discovering upgrades in the current Compressed Sensing procedure that utilizations Non Adaptive Projection Matrix rule. Normal Frame Signal-to-Noise Ratio (AFSNR) is intended to evaluate the show of the Frame-Based Adaptive Compressed Sensing with the Non-Adaptive Compressed Sensing (CS). It is a developing sign securing strategy and straight gathers the signs in a compacted shape on the off chance that they are meager on some specific premise. Proposed approach utilizes Adaptive Projection Matrix in light of edge examination which gives fundamentally enhanced discourse recreation quality and decreases the noise levels.

Long-period seafloor seismology and deformation under ocean waves

1999 ◽  
Vol 89 (6) ◽  
pp. 1535-1542 ◽  
Author(s):  
Spahr C. Webb ◽  
Wayne C. Crawford
Keyword(s):  
Shallow Water ◽  
Signal To Noise Ratio ◽  
Wave Spectrum ◽  
Vertical Component ◽  
Ocean Waves ◽  
Vertical Acceleration ◽  
Noise Levels ◽  
Signal To Noise ◽  
Long Period ◽  
Noise Ratio

Abstract The deformation of the seafloor under loading by long-period ocean waves raises vertical component noise levels at the deep seafloor by 20 to 30 dB above noise levels at good continental sites in the band from 0.001 to 0.04 Hz. This noise substantially limits the detection threshold and signal-to-noise ratio for long-period phases of earthquakes observed by seafloor seismometers. Borehole installation significantly improves the signal-to-noise ratio only if the sensor is installed at more than 1 km below the seafloor because the deformation signal decays slowly with depth. However, the vertical-component deformation signal can be predicted and suppressed using seafloor measurements of pressure fluctuations observed by differential pressure gauges. The pressure observations of ocean waves are combined with measurements of the transfer function between vertical acceleration and pressure to predict the vertical component deformation signal. Subtracting the predicted deformation signal from pressure observations can reduce vertical component noise levels near 0.01 Hz by more than 25 dB, significantly improving signal-to-noise ratios for long-period phases. There is also a horizontal-component deformation signal but it is smaller than the vertical-component signal and only significant in shallow water (&lt;1-km deep). The amplitude of the deformation signal depends both on the long-period ocean-wave spectrum and the elastic-wave velocities in the oceanic crust. It is largest at sedimented sites and in shallow water.

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