The effect of signal duration on frequency discrimination at low signal-to-noise ratios in different conditions of interaural phase

1990 ◽  
Vol 48 (3) ◽  
pp. 201-207 ◽  
Author(s):  
G.B Henning ◽  
S Wartini
Keyword(s):  
Frequency Discrimination ◽  
Signal Duration ◽  
Signal To Noise ◽  
Interaural Phase

Relation of Masked Threshold to Signal-Duration for Various Interaural Phase-Combinations

1958 ◽  
Vol 71 (1) ◽  
pp. 283 ◽  
Author(s):  
Hugh C. Blodgett ◽  
Lloyd A. Jeffress ◽  
Robert W. Taylor
Keyword(s):  
Signal Duration ◽  
Interaural Phase

scholarly journals Bounds on the Transmit Power of b-Modulated NFDM Systems in Anomalous Dispersion Fiber

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 639 ◽  
Author(s):  
Shrinivas Chimmalgi ◽  
Sander Wahls
Keyword(s):  
Upper Bound ◽  
Fiber Optic ◽  
Anomalous Dispersion ◽  
Signal Duration ◽  
Nonlinear Frequency ◽  
Frequency Division ◽  
Signal To Noise ◽  
Transmit Power ◽  
Spectral Singularities ◽  
Nonlinear Spectrum

The performance of various nonlinear frequency division multiplexed (NFDM) fiber-optic transmission systems has been observed to decrease with increasing signal duration. For a class of NFDM systems known as b-modulators, we show that the nonlinear bandwidth, signal duration, and power are coupled when singularities in the nonlinear spectrum are avoided. When the nonlinear bandwidth is fixed, the coupling results in an upper bound on the transmit power that decreases with increasing signal duration. Signal-to-noise ratios are consequently expected to decrease, which can help explain drops in performance observed in practice. Furthermore, we show that there is often a finite bound on the transmit power of b-modulators even if spectral singularities are allowed.

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 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>

Auditory Acuity in the Sea Catfish (Arius Felis)

1982 ◽  
Vol 96 (1) ◽  
pp. 367-376
Author(s):  
WILLIAM N. TAVOLGA
Keyword(s):  
Avoidance Conditioning ◽  
Broad Band ◽  
Reference Signal ◽  
Frequency Discrimination ◽  
Signal To Noise ◽  
Spectrum Level ◽  
Band Noise ◽  
Auditory Acuity

Frequency discrimination limens and signal-to-noise ratios were determined for the sea catfish, Arius fetis, using avoidance-conditioning techniques. The lowest frequency discrimination limens had values of about 2.5% at 100 Hz. Other determinations were 3.5 % at 200 Hz, and 5 % at 400 Hz, but these values were significantly greater if the test frequencies were higher than the reference. Signal-to-noise ratios were 14 dB at 100 Hz, 18 dB at 200 Hz, and 24 dB at 400 Hz, with reference to the spectrum level of broad-band noise. These findings, and previous measurements of acuity, are discussed in relation to echolocation in Arius, which is known to involve sounds in the 100–200 Hz range.

Radiation Damage, Contrast and Statistics in High Resolution Biological Electron Microscopy

1970 ◽  
Vol 28 ◽  
pp. 260-261
Author(s):  
Robert M. Glaeser
Keyword(s):  
High Resolution ◽  
Particle Flux ◽  
Unit Area ◽  
Signal To Noise ◽  
Resolution Image ◽  
High Resolution Image ◽  
Pass Through ◽  
Counting Statistics ◽  
The Relationship ◽  
Picture Element

It is well known that a large flux of electrons must pass through a specimen in order to obtain a high resolution image while a smaller particle flux is satisfactory for a low resolution image. The minimum particle flux that is required depends upon the contrast in the image and the signal-to-noise (S/N) ratio at which the data are considered acceptable. For a given S/N associated with statistical fluxtuations, the relationship between contrast and “counting statistics” is s131_eqn1, where C = contrast; r2 is the area of a picture element corresponding to the resolution, r; N is the number of electrons incident per unit area of the specimen; f is the fraction of electrons that contribute to formation of the image, relative to the total number of electrons incident upon the object.

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