scholarly journals Decoding Speech and Music Stimuli from the Frequency Following Response

2019 ◽  
Author(s):  
Steven Losorelli ◽  
Blair Kaneshiro ◽  
Gabriella A. Musacchia ◽  
Nikolas H. Blevins ◽  
Matthew B. Fitzgerald
Keyword(s):  
Time Domain ◽  
Auditory Perception ◽  
Objective Assessment ◽  
Perceptual Identification ◽  
Complex Sounds ◽  
Linear Discriminant ◽  
Speech Stimuli ◽  
Fundamental Frequencies ◽  
The Time Domain ◽  
Different Response

AbstractThe ability to differentiate complex sounds is essential for communication. Here, we propose using a machine-learning approach, called classification, to objectively evaluate auditory perception. In this study, we recorded frequency following responses (FFRs) from 13 normal-hearing adult participants to six short music and speech stimuli sharing similar fundamental frequencies but varying in overall spectral and temporal characteristics. Each participant completed a perceptual identification test using the same stimuli. We used linear discriminant analysis to classify FFRs. Results showed statistically significant FFR classification accuracies using both the full response epoch in the time domain (72.3% accuracy, p < 0.001) as well as real and imaginary Fourier coefficients up to 1 kHz (74.6%, p < 0.001). We classified decomposed versions of the responses in order to examine which response features contributed to successful decoding. Classifier accuracies using Fourier magnitude and phase alone in the same frequency range were lower but still significant (58.2% and 41.3% respectively, p < 0.001). Classification of overlapping 20-msec subsets of the FFR in the time domain similarly produced reduced but significant accuracies (42.3%–62.8%, p < 0.001). Participants’ mean perceptual responses were most accurate (90.6%, p < 0.001). Confusion matrices from FFR classifications and perceptual responses were converted to distance matrices and visualized as dendrograms. FFR classifications and perceptual responses demonstrate similar patterns of confusion across the stimuli. Our results demonstrate that classification can differentiate auditory stimuli from FFR responses with high accuracy. Moreover, the reduced accuracies obtained when the FFR is decomposed in the time and frequency domains suggest that different response features contribute complementary information, similar to how the human auditory system is thought to rely on both timing and frequency information to accurately process sound. Taken together, these results suggest that FFR classification is a promising approach for objective assessment of auditory perception.

Decomposition of Gear Motion Signals and Its Application to Gearbox Diagnostics

1995 ◽  
Vol 117 (3A) ◽  
pp. 363-369 ◽  
Author(s):  
W. J. Wang ◽  
P. D. McFadden
Keyword(s):  
Time Domain ◽  
Vibration Signal ◽  
Error Signal ◽  
Dynamic Measurements ◽  
Motion Error ◽  
Gear Teeth ◽  
Fundamental Frequencies ◽  
The Time Domain ◽  
Fault Information ◽  
Early Damage

The decomposition of gear motion and the related dynamic measurements for the condition monitoring and fault diagnosis of gearboxes are described. The motion error signal is separated according to fundamental frequencies into the harmonic error and the residual error, which are used to quantify the gear condition. High-order accelerations, such as jerk, are considered and shown to be more sensitive to some classes of early damage to gear teeth. Analysis of the time domain average of a gearbox casing vibration signal enables early detection of gear damage. Several methods to represent and enhance the fault information in the signal are introduced, based on the representation of different forms of the motion errors.

scholarly journals Research on Prediction Algorithm of Employees’ Psychological Stress Based on Multifeature Fusion

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lijun Chang
Keyword(s):  
Frequency Domain ◽  
Psychological Stress ◽  
Time Domain ◽  
Evidence Theory ◽  
Prediction Algorithm ◽  
Ecg Signal ◽  
Linear Features ◽  
Linear Discriminant ◽  
Stress Prediction ◽  
The Time Domain

A multifeature fusion-based enterprise employee psychological stress prediction algorithm is suggested to address the concerns of low prediction accuracy, long duration, and poor results in current psychological stress prediction approaches. Examine ECG signal generation and properties, as well as the notion and causes of heart rate variability. The ECG signal is gathered according to the psychological stress reaction mechanism, and the digital filter is utilized to filter and preprocess the noise interference of the ECG signal. The linear discriminant analysis algorithm extracts the time domain linear features, frequency domain linear features, and nonlinear features of the ECG signal and then selects the ECG signal characteristics. D-S evidence theory is used to fuse the time domain linear characteristics, frequency domain linear characteristics, and nonlinear characteristics of the ECG signal, construct the psychological stress prediction model, obtain the final result of psychological stress state prediction, and realize the psychological stress prediction of enterprise employees, all based on multifeature fusion technology. The results of the experiments reveal that the suggested algorithm has a greater predictive effect on employee psychological stress, allowing it to enhance forecast accuracy and reduce prediction time.

Apodisation in the time domain

1992 ◽  
Vol 2 (4) ◽  
pp. 615-620
Author(s):  
G. W. Series
Keyword(s):  
Time Domain ◽  
The Time Domain

JOINT INTERPRETATION OF AIRBORNE ELECTROMAGNETIC DATA IN THE TIME DOMAIN AND FREQUENCY DOMAIN

2018 ◽  
Vol 12 (7-8) ◽  
pp. 76-83
Author(s):  
E. V. KARSHAKOV ◽  
J. MOILANEN
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Frequency Interval ◽  
Single Spectrum ◽  
Simultaneous Inversion ◽  
Homogeneous Half Space ◽  
Time Domain Data ◽  
The Time Domain

Тhe advantage of combine processing of frequency domain and time domain data provided by the EQUATOR system is discussed. The heliborne complex has a towed transmitter, and, raised above it on the same cable a towed receiver. The excitation signal contains both pulsed and harmonic components. In fact, there are two independent transmitters operate in the system: one of them is a normal pulsed domain transmitter, with a half-sinusoidal pulse and a small "cut" on the falling edge, and the other one is a classical frequency domain transmitter at several specially selected frequencies. The received signal is first processed to a direct Fourier transform with high Q-factor detection at all significant frequencies. After that, in the spectral region, operations of converting the spectra of two sounding signals to a single spectrum of an ideal transmitter are performed. Than we do an inverse Fourier transform and return to the time domain. The detection of spectral components is done at a frequency band of several Hz, the receiver has the ability to perfectly suppress all sorts of extra-band noise. The detection bandwidth is several dozen times less the frequency interval between the harmonics, it turns out thatto achieve the same measurement quality of ground response without using out-of-band suppression you need several dozen times higher moment of airborne transmitting system. The data obtained from the model of a homogeneous half-space, a two-layered model, and a model of a horizontally layered medium is considered. A time-domain data makes it easier to detect a conductor in a relative insulator at greater depths. The data in the frequency domain gives more detailed information about subsurface. These conclusions are illustrated by the example of processing the survey data of the Republic of Rwanda in 2017. The simultaneous inversion of data in frequency domain and time domain can significantly improve the quality of interpretation.

scholarly journals Broadband spectroscopy of astrophysical ice analogues

2019 ◽  
Vol 629 ◽  
pp. A112 ◽  
Author(s):  
B. M. Giuliano ◽  
A. A. Gavdush ◽  
B. Müller ◽  
K. I. Zaytsev ◽  
T. Grassi ◽  
...  
Keyword(s):  
Refractive Index ◽  
Optical Properties ◽  
Time Domain ◽  
Complex Refractive Index ◽  
Far Infrared ◽  
Infrared Region ◽  
Thz Radiation ◽  
The Real ◽  
Thz Range ◽  
The Time Domain

Context. Reliable, directly measured optical properties of astrophysical ice analogues in the infrared and terahertz (THz) range are missing from the literature. These parameters are of great importance to model the dust continuum radiative transfer in dense and cold regions, where thick ice mantles are present, and are necessary for the interpretation of future observations planned in the far-infrared region. Aims. Coherent THz radiation allows for direct measurement of the complex dielectric function (refractive index) of astrophysically relevant ice species in the THz range. Methods. We recorded the time-domain waveforms and the frequency-domain spectra of reference samples of CO ice, deposited at a temperature of 28.5 K and annealed to 33 K at different thicknesses. We developed a new algorithm to reconstruct the real and imaginary parts of the refractive index from the time-domain THz data. Results. The complex refractive index in the wavelength range 1 mm–150 μm (0.3–2.0 THz) was determined for the studied ice samples, and this index was compared with available data found in the literature. Conclusions. The developed algorithm of reconstructing the real and imaginary parts of the refractive index from the time-domain THz data enables us, for the first time, to determine the optical properties of astrophysical ice analogues without using the Kramers–Kronig relations. The obtained data provide a benchmark to interpret the observational data from current ground-based facilities as well as future space telescope missions, and we used these data to estimate the opacities of the dust grains in presence of CO ice mantles.

EPR light beams and non-Gaussian quantum distributions in the time domain

2009 ◽  
Vol 6 (7) ◽  
pp. 577-580
Author(s):  
N. H. Adamyan ◽  
H. H. Adamyan ◽  
G. Yu. Kryuchkyan
Keyword(s):  
Time Domain ◽  
Non Gaussian ◽  
The Time Domain ◽  
Light Beams ◽  
Quantum Distributions

Separating Multiple Moving Sources by Microphone Array Signals for Wayside Acoustic Fault Diagnosis

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Wei Xiong ◽  
Qingbo He ◽  
Zhike Peng
Keyword(s):  
Fault Diagnosis ◽  
Time Domain ◽  
Feature Matching ◽  
Matching Pursuit ◽  
Microphone Array ◽  
Time Frequency ◽  
Moving Sources ◽  
The Time Domain ◽  
Envelope Spectrum ◽  
Threshold Setting

Wayside acoustic defective bearing detector (ADBD) system is a potential technique in ensuring the safety of traveling vehicles. However, Doppler distortion and multiple moving sources aliasing in the acquired acoustic signals decrease the accuracy of defective bearing fault diagnosis. Currently, the method of constructing time-frequency (TF) masks for source separation was limited by an empirical threshold setting. To overcome this limitation, this study proposed a dynamic Doppler multisource separation model and constructed a time domain-separating matrix (TDSM) to realize multiple moving sources separation in the time domain. The TDSM was designed with two steps of (1) constructing separating curves and time domain remapping matrix (TDRM) and (2) remapping each element of separating curves to its corresponding time according to the TDRM. Both TDSM and TDRM were driven by geometrical and motion parameters, which would be estimated by Doppler feature matching pursuit (DFMP) algorithm. After gaining the source components from the observed signals, correlation operation was carried out to estimate source signals. Moreover, fault diagnosis could be carried out by envelope spectrum analysis. Compared with the method of constructing TF masks, the proposed strategy could avoid setting thresholds empirically. Finally, the effectiveness of the proposed technique was validated by simulation and experimental cases. Results indicated the potential of this method for improving the performance of the ADBD system.

scholarly journals Diagnostically Oriented Experiments and Modelling of Switched Reluctance Motor Dynamic Eccentricity

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3857
Author(s):  
Jakub Lorencki ◽  
Stanisław Radkowski ◽  
Szymon Gontarz
Keyword(s):  
Time Domain ◽  
Test Bench ◽  
Switched Reluctance Motor ◽  
Industrial Applications ◽  
Switched Reluctance ◽  
Static And Dynamic Analysis ◽  
Geometry Model ◽  
Reluctance Motor ◽  
Dynamic Eccentricity ◽  
The Time Domain

The article compares the results of experimental and modelling research of switched reluctance motor at two different operational states: one proper and one with mechanical fault, i.e., with dynamic eccentricity of the rotor. The experiments were carried out on a test bench and then the results were compared with mathematical modelling of quasi-static and dynamic analysis of 2D geometry model. Finally, it was examined how the operation with dynamic eccentricity fault of the motor affected its main physical parameter—the phase current. The analysis was presented in the frequency domain using the Fast Fourier Transform (FFT); however, individual current waveforms in the time domain are also shown for comparison. Applying results of the research could increase reliability of the maintenance of SRM and enhance its application in vehicles for special purposes as well as its military and industrial applications.

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