Wiener filtering (with emphasis on frequency-domain approaches)

Author(s):  
R.J. Bhansali ◽  
D. Karavellas
2019 ◽  
Vol 8 (2S11) ◽  
pp. 1058-1062

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.


Geophysics ◽  
1989 ◽  
Vol 54 (12) ◽  
pp. 1607-1613 ◽  
Author(s):  
R. O. Hansen ◽  
R. S. Pawlowski

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.


Author(s):  
Mohammad Reza Asharif ◽  
Rui Chen

In this chapter, we shall study adaptive digital filtering (ADF) and its application to acoustic echo canceling (AEC). At first, Wiener filtering and algorithms such as LMS in the time domain for ADF are explained. Then, to decrease the computational complexity, the frequency domain algorithms such as FDAF and FBAF will be studied. To challenge the double-talk problem in AEC, we will also introduce various algorithms by processing the correlation function of the signal. The proposed algorithms here are CLMS, ECLMS, and using frequency domain is FECLMS, and using wavelet transform is WECLMS. Each of these algorithms has its own merits, and they will be evaluated. At the end of this chapter a new system for room-acoustic partitioning is proposed. This new system is called smart acoustic room (SAR). The SAR will also be used in AEC with double-talk condition. The authors wish to gather all aspects in studying ADF and their use in AEC by going very deep into theoretical details as well as considering more practical and feasible applications considering real-time implementation.


2007 ◽  
Author(s):  
Michael K. Broadhead ◽  
Christopher L. Liner ◽  
Tadeusz J. Ulrych

1990 ◽  
Vol 26 (8) ◽  
pp. 1863-1863
Author(s):  
Paul Marschall ◽  
Baldur Barczewski
Keyword(s):  

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