Modified regularised spectral estimation in short-time-recorded data

1995 ◽  
Vol 31 (17) ◽  
pp. 1413-1415 ◽  
Author(s):  
Jun-Seok Lim ◽  
K.M. Sung ◽  
Han-Su Kim
Keyword(s):  
Spectral Estimation ◽  
Recorded Data ◽  
Short Time

Vortex Characterization and Identification by Ultrasound Doppler

1981 ◽  
Vol 3 (3) ◽  
pp. 271-293 ◽  
Author(s):  
L. J. D'Luna ◽  
V. L. Newhouse
Keyword(s):  
Spectral Estimation ◽  
Entropy Method ◽  
Channel Flows ◽  
Spectral Estimates ◽  
System A ◽  
Novel Approach ◽  
Doppler Signals ◽  
Invasive Method ◽  
Short Time ◽  
Pulsed Rf

The detection of vortices is of potential interest in physiology (e.g. the detection of weak stenoses), and in fluid mechanics. In this paper a non-invasive method of detecting vortices in channel flows using pulsed RF Doppler ultrasound is described. A novel approach involving hybrid operation is taken in implementing a directional Doppler system. A scattering model of a vortex crossing an ultrasound beam is presented and theoretical simulations of the Doppler signals show good agreement with experiment. Experimental results showing the detection of both periodic and isolated vortices in channel flows are given. The Autoregressive or Maximum Entropy Method of spectral estimation is used to obtain the spectral estimates of the Doppler signals over short time intervals. It is shown that these spectral estimates can be used to estimate the velocity profiles of the detected vortices.

Super-resolution spectral estimation in short-time non-contact vital sign measurement

2015 ◽  
Vol 86 (4) ◽  
pp. 044708 ◽  
Author(s):  
Li Sun ◽  
Yusheng Li ◽  
Hong Hong ◽  
Feng Xi ◽  
Weidong Cai ◽  
...  
Keyword(s):  
Vital Sign ◽  
Spectral Estimation ◽  
Super Resolution ◽  
Vital Sign Measurement ◽  
Short Time

scholarly journals New Features Using Robust MVDR Spectrum of Filtered Autocorrelation Sequence for Robust Speech Recognition

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Sanaz Seyedin ◽  
Seyed Mohammad Ahadi ◽  
Saeed Gazor
Keyword(s):  
Speech Recognition ◽  
Spectral Estimation ◽  
Estimation Method ◽  
Minimum Variance ◽  
Mel Frequency Cepstral Coefficients ◽  
Feature Extraction Method ◽  
Minimum Variance Distortionless Response ◽  
Robust Feature Extraction ◽  
Noise Robust ◽  
Short Time

This paper presents a novel noise-robust feature extraction method for speech recognition using the robust perceptual minimum variance distortionless response (MVDR) spectrum of temporally filtered autocorrelation sequence. The perceptual MVDR spectrum of the filtered short-time autocorrelation sequence can reduce the effects of residue of the nonstationary additive noise which remains after filtering the autocorrelation. To achieve a more robust front-end, we also modify the robust distortionless constraint of the MVDR spectral estimation method via revised weighting of the subband power spectrum values based on the sub-band signal to noise ratios (SNRs), which adjusts it to the new proposed approach. This new function allows the components of the input signal at the frequencies least affected by noise to pass with larger weights and attenuates more effectively the noisy and undesired components. This modification results in reduction of the noise residuals of the estimated spectrum from the filtered autocorrelation sequence, thereby leading to a more robust algorithm. Our proposed method, when evaluated on Aurora 2 task for recognition purposes, outperformed all Mel frequency cepstral coefficients (MFCC) as the baseline, relative autocorrelation sequence MFCC (RAS-MFCC), and the MVDR-based features in several different noisy conditions.

A Review of Time-Frequency Analysis Techniques for Estimation of Group Velocities

1993 ◽  
Vol 64 (2) ◽  
pp. 157-167 ◽  
Author(s):  
Argun H. Kocaoglu ◽  
Leland T. Long
Keyword(s):  
Fourier Transform ◽  
Wigner Distribution ◽  
Spectral Estimation ◽  
Moving Window ◽  
Window Length ◽  
Short Time Fourier Transform ◽  
Time Frequency ◽  
Analysis Techniques ◽  
Short Time ◽  
Group Velocities

Abstract Time-frequency analysis techniques, including the classical use of zero crossings to measure period, have been widely used in seismology for the estimation of surface wave group velocities. Group velocity estimation by the short-time Fourier transform and the multiple filter techniques are equivalent. Although these techniques are used most often, their resolution is limited. The resolution is controlled by the window length in the short time Fourier transform and the filter band width in the multiple filter technique. The moving-window autoregressive spectral estimation provides the highest resolution with the shortest possible window length by predicting the properties of the signal outside the analysis window; however, high resolution is obtained at the expense of uncertainty in the amplitude. Recently, the Wigner distribution has been introduced as a tool for mapping dispersed surface waves into the time-frequency domain. Resolution of the Wigner distribution is comparable to that of the moving-window autoregressive spectral estimation. When the spectral density at a given time contains two or more dominant frequencies, their interference causes the Wigner distribution to introduce spurious spectral peaks complicating the interpretation. The Choi-Williams distribution, in which these interference effects are minimized, can be used for such dispersed signals. However, the implementation is computationally complex and the distribution offers only a medium resolution.

Improved modelling of suspended solids discharge from asphalt surface during storm event

1996 ◽  
Vol 33 (4-5) ◽  
pp. 363-369 ◽  
Author(s):  
Ana Tomanovic ◽  
Cedo Maksimovic
Keyword(s):  
Statistical Analysis ◽  
Suspended Solids ◽  
Storm Event ◽  
Time Intervals ◽  
Process Dynamics ◽  
Physically Based ◽  
Recorded Data ◽  
Urban Catchments ◽  
Short Time ◽  
Main Factor

Measurements, aiming at the investigation of pollution wash-off from a single asphalt area which is drained into one gullypot, have been carried out at two similar experimental urban catchments: in Lund, Sweden, and in Belgrade, Yugoslavia. At both sites the continuous measurements of rainfall intensity, storm runoff and four water quality characteristics (suspended solids, pH-factor, conductivity and temperature) were carried out, using a similar method and similar equipment. To reach the required level of process dynamics, the data were recorded at short time intervals (10 sec) during a storm event. Statistical analysis of reliably measured data showed the main factor that affect surface solids build-up and wash-off. Based on it, a new physically based mathematical model of suspended solids wash-off has been developed. The model was calibrated and verified for both catchments. The brief description of the measurements, statistical analysis of recorded data, and the model, is presented in the paper.

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