Predictive deconvolution by frequency domain Wiener filtering

2007 ◽  
Author(s):  
Michael K. Broadhead ◽  
Christopher L. Liner ◽  
Tadeusz J. Ulrych
Keyword(s):  
Frequency Domain ◽  
Wiener Filtering ◽  
Predictive Deconvolution

Predictive deconvolution in the frequency domain

1988 ◽  
Author(s):  
Tad J. Ulrych ◽  
Milton Porsani ◽  
Jacob T. Fokkema ◽  
W. Scott ◽  
P. Leaney ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Predictive Deconvolution

scholarly journals Wiener Filtering in Frequency Domain to Enhance Speech Corrupted by Colored Noise

2019 ◽  
Vol 8 (2S11) ◽  
pp. 1058-1062
Keyword(s):  
Frequency Domain ◽  
Performance Measures ◽  
Speech Enhancement ◽  
Colored Noise ◽  
Quality Measures ◽  
Wiener Filtering ◽  
Spectral Distortion ◽  
Gain Function ◽  
Objective Quality ◽  
Log Likelihood

This paper presents a method for speech enhancement to predict speech quality in presence of highly non-stationary scenarios using basic wiener filtering in frequency domain with an adaptive gain function under eight different noises at three different ranges of input SNR. Its performance is evaluated in terms of objective quality measures like LPC based spectral distortion measures are Cepstrum Distance, Itakura Saito and Log Likelihood Ratio. This method was tested using Noizeous database, its performance measures were compared against spectral subtractive type algorithms and it shows its improvements in terms of objective quality measures.

Reduction to the pole at low latitudes by Wiener filtering

Geophysics ◽  
1989 ◽  
Vol 54 (12) ◽  
pp. 1607-1613 ◽  
Author(s):  
R. O. Hansen ◽  
R. S. Pawlowski
Keyword(s):  
Frequency Domain ◽  
Synthetic Data ◽  
Wiener Filtering ◽  
Magnetic Data ◽  
Noise Power ◽  
Low Latitude ◽  
High Quality ◽  
Computational Load ◽  
Low Latitudes ◽  
Reduction To The Pole

Using simple estimates of the signal and noise power from gridded magnetic data, we design regulated frequency‐domain operators for reduction to the pole at low magnetic latitudes. These operators suppress the artifacts along the direction of the magnetic declination associated with the conventional reduction‐to‐the‐pole procedure, with negligible increase in computational load. The new procedure is applied to produce high‐quality reductions to the pole for noisy low‐latitude synthetic data and for magnetic data from the Dixon Seamount.

A critique of seismic deconvolution methods

Geophysics ◽  
1984 ◽  
Vol 49 (12) ◽  
pp. 2109-2116 ◽  
Author(s):  
Andrejs Jurkevics ◽  
Ralphe Wiggins
Keyword(s):  
Pulse Compression ◽  
Adaptive Methods ◽  
Substantial Improvement ◽  
Wiener Filtering ◽  
Minimum Entropy ◽  
Seismic Wavelet ◽  
Predictive Deconvolution ◽  
Phase Condition ◽  
Signal Distortions ◽  
Zero Phase

Different seismic pulse compression methods are evaluated. These include several algorithms for computing prediction error filters: Wiener filtering, Burg’s method, the [Formula: see text] norm criterion, Kalman filtering, and two time‐adaptive methods. Algorithms which do not assume a minimum‐phase condition for the seismic wavelet include minimum entropy, homomorphic, and zero‐phase deconvolution. The sensitivity of these algorithms is examined for various earth reflectivity functions, source waveforms, and signal distortions. The results indicate that standard Wiener predictive deconvolution is robust under a wide variety of input conditions. However, a substantial improvement in pulse compression can be obtained by the Burg algorithm under conditions of short data segments and by minimum entropy deconvolution for seismograms consisting of mixed‐phase wavelets combined with sparse reflectivity series.

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