scholarly journals Wiener Filters for the Reconditioning of Old Speech Recordings Under Uncertainty

2018 ◽  
Author(s):  
Horia-Nicolai L. Teodorescu
Keyword(s):  
Wiener Filters

A simple way for producing holographic filters suitable for image improvement

1978 ◽  
Vol 36 (1) ◽  
pp. 226-227
Author(s):  
K.-H. Herrmann ◽  
E. Reuber ◽  
P. Schiske
Keyword(s):  
Transfer Functions ◽  
Diffraction Order ◽  
Lateral Position ◽  
Simple Method ◽  
Spatial Frequencies ◽  
Resolution Electron ◽  
Wiener Filters ◽  
Image Improvement ◽  
Optical Reconstruction ◽  
Set Up

Aposteriori deblurring of high resolution electron micrographs of weak phase objects can be performed by holographic filters [1,2] which are arranged in the Fourier domain of a light-optical reconstruction set-up. According to the diffraction efficiency and the lateral position of the grating structure, the filters permit adjustment of the amplitudes and phases of the spatial frequencies in the image which is obtained in the first diffraction order.In the case of bright field imaging with axial illumination, the Contrast Transfer Functions (CTF) are oscillating, but real. For different imageforming conditions and several signal-to-noise ratios an extensive set of Wiener-filters should be available. A simple method of producing such filters by only photographic and mechanical means will be described here.A transparent master grating with 6.25 lines/mm and 160 mm diameter was produced by a high precision computer plotter. It is photographed through a rotating mask, plotted by a standard plotter.

THE DETERMINATION OF DIGITAL WIENER FILTERS BY MEANS OF GRADIENT METHODS

Geophysics ◽  
1973 ◽  
Vol 38 (2) ◽  
pp. 310-326 ◽  
Author(s):  
R. J. Wang ◽  
S. Treitel
Keyword(s):  
Seismic Data ◽  
High Speed ◽  
Gradient Methods ◽  
Wiener Filter ◽  
Gradient Algorithm ◽  
Rapid Convergence ◽  
True Solution ◽  
Peripheral Device ◽  
Wiener Filters

The normal equations for the discrete Wiener filter are conventionally solved with Levinson’s algorithm. The resultant solutions are exact except for numerical roundoff. In many instances, approximate rather than exact solutions satisfy seismologists’ requirements. The so‐called “gradient” or “steepest descent” iteration techniques can be used to produce approximate filters at computing speeds significantly higher than those achievable with Levinson’s method. Moreover, gradient schemes are well suited for implementation on a digital computer provided with a floating‐point array processor (i.e., a high‐speed peripheral device designed to carry out a specific set of multiply‐and‐add operations). Levinson’s method (1947) cannot be programmed efficiently for such special‐purpose hardware, and this consideration renders the use of gradient schemes even more attractive. It is, of course, advisable to utilize a gradient algorithm which generally provides rapid convergence to the true solution. The “conjugate‐gradient” method of Hestenes (1956) is one of a family of algorithms having this property. Experimental calculations performed with real seismic data indicate that adequate filter approximations are obtainable at a fraction of the computer cost required for use of Levinson’s algorithm.

Subspace Expansion and the Equivalence of Conjugate Direction and Multistage Wiener Filters

2008 ◽  
Vol 56 (10) ◽  
pp. 5013-5019 ◽  
Author(s):  
L.L. Scharf ◽  
E.K.P. Chong ◽  
M.D. Zoltowski ◽  
J.S. Goldstein ◽  
I.S. Reed
Keyword(s):  
Conjugate Direction ◽  
Wiener Filters

scholarly journals Application of the Wiener filter to magnetic profiling in the volcanic environment of Mt. Etna (Italy)

1996 ◽  
Vol 39 (1) ◽  
Author(s):  
C. Del Negro
Keyword(s):  
Synthetic Data ◽  
Wiener Filter ◽  
Magnetic Anomalies ◽  
Fault System ◽  
Volcanic Area ◽  
Wiener Filters ◽  
Mt Etna ◽  
Band Pass ◽  
Magnetic Profile ◽  
Mean Square Error Criterion

The frequency-domain Wiener filtering was applied to magnetic anomalies in the volcanic area of Mt. Etna. This filter, under suitable conditions (additive noise, linear processing and mean-square error criterion), can furnish an effective tool for discriminating the geologic feature of interest (the signal) from the noise. The filter was first tested with synthetic data. Afterwards it was applied to a magnetic profile carried out across the principal fault system of the Mt. Etna volcano, that hosted the dykes feeding both the 1989 and the 1991-93 eruptions. The magnetic anomalies linked to the volcanic section and those linked to the contact between the clay basement and the lava coverage show significant spectral overlap. Thus by estimating the power spectrum of the signal, obtained resolving the forward problem, a least-squares Wiener filter has been designed. In such context, it was possible to verify the effectiveness of Wiener filters, whereas traditional band-pass filtering proved inadequate. In fact, analysis of the noise showed that all the meaningful components of the observed magnetic field were resolved. The results put further constraints on location and geometry of the shallow plumbing system of Mt. Etna.

scholarly journals New insights on the optimality of parameterized Wiener filters for speech enhancement applications

2019 ◽  
Vol 109 ◽  
pp. 46-54 ◽  
Author(s):  
Rafael Attili Chiea ◽  
Márcio Holsbach Costa ◽  
Guillaume Barrault
Keyword(s):  
Speech Enhancement ◽  
Wiener Filters
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