FEEDFORWARD AND FEEDBACK CONTROL OF SOUND AND VIBRATION—A WIENER FILTER APPROACH

2001 ◽  
Vol 246 (2) ◽  
pp. 281-296 ◽  
Author(s):  
M.J. BRENNAN ◽  
S.-M. KIM
Keyword(s):  
Feedback Control ◽  
Wiener Filter ◽  
Filter Approach

A Wiener filter approach to shape from shading

2017 ◽  
Author(s):  
Oscar E. Castillo ◽  
Jorge Luis Flores Nuñez ◽  
Jose A. Muñoz ◽  
Ricardo Legarda
Keyword(s):  
Wiener Filter ◽  
Shape From Shading ◽  
Filter Approach

A KALMAN FILTER APPROACH TO THE DECONVOLUTION OF SEISMIC SIGNALS

Geophysics ◽  
1974 ◽  
Vol 39 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Norman D. Crump
Keyword(s):  
Kalman Filter ◽  
Wiener Filter ◽  
Seismic Signal ◽  
Seismic Signals ◽  
Discrete State ◽  
Seismic Wavelet ◽  
State Variable ◽  
Deconvolution Technique ◽  
Reflectivity Function ◽  
Filter Approach

It is common practice to model a reflection seismogram as a convolution of the reflectivity function of the earth and an energy waveform referred to as the seismic wavelet. The objective of the deconvolution technique described here is to extract the reflectivity function from the reflection seismogram. The most common approach to deconvolution has been the design of inverse filters based on Wiener filter theory. Some of the disadvantages of the inverse filter approach may be overcome by using a state variable representation of the earth’s reflectivity function and the seismic signal generating process. The problem is formulated in discrete state variable form to facilitate digital computer processing of digitized seismic signals. The discrete form of the Kalman filter is then used to generate an estimate of the reflectivity function. The principal advantages of this technique are its capability for handling continually time‐varying models, its adaptability to a large class of models, its suitability for either single or multi‐channel processing, and its potentially high‐resolution capabilities. Examples based on both synthetic and field seismic data illustrate the feasibility of the method.

scholarly journals Multichannel speaker interference reduction using frequency domain adaptive filtering

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Patrick Meyer ◽  
Samy Elshamy ◽  
Tim Fingscheidt
Keyword(s):  
Wiener Filter ◽  
Echo Cancellation ◽  
Filter Method ◽  
Noise Component ◽  
Interference Reduction ◽  
Live Music ◽  
Audio Recordings ◽  
Automatic Transcription ◽  
Component Estimation ◽  
Filter Approach

Abstract Microphone leakage or crosstalk is a common problem in multichannel close-talk audio recordings (e.g., meetings or live music performances), which occurs when a target signal does not only couple into its dedicated microphone, but also in all other microphone channels. For further signal processing such as automatic transcription of a meeting, a multichannel speaker interference reduction is required in order to eliminate the interfering speech signals in the microphone channels. The contribution of this paper is twofold: First, we consider multichannel close-talk recordings of a three-person meeting scenario with various different crosstalk levels. In order to eliminate the crosstalk in the target microphone channel, we extend a multichannel Wiener filter approach, which considers all individual microphone channels. Therefore, we integrate an adaptive filter method, which was originally proposed for acoustic echo cancellation (AEC), in order to obtain a well-performing interferer (noise) component estimation. This results in an improved speech-to-interferer ratio by up to 2.7 dB at constant or even better speech component quality. Second, since an AEC method requires typically clean reference channels, we investigate and report findings why the AEC algorithm is able to successfully estimate the interfering signals and the room impulse responses between the microphones of the interferer and the target speakers even though the reference signals are themselves disturbed by crosstalk in the considered meeting scenario.

A Wiener filter approach to the binaural reproduction of stereo sound

2003 ◽  
Vol 114 (6) ◽  
pp. 3179-3188 ◽  
Author(s):  
Sang-Myeong Kim ◽  
Semyung Wang
Keyword(s):  
Wiener Filter ◽  
Filter Approach

scholarly journals A Monte Carlo comparison between template-based and Wiener-filter CMB dipole estimators

2020 ◽  
Vol 643 ◽  
pp. A179
Author(s):  
H. Thommesen ◽  
K. J. Andersen ◽  
R. Aurlien ◽  
R. Banerji ◽  
M. Brilenkov ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Wiener Filter ◽  
Higher Order ◽  
Data Sets ◽  
Microwave Background ◽  
Dipole Estimation ◽  
Filter Approach ◽  
Relative Differences ◽  
Best Fit

We review and compare two different cosmic microwave background (CMB) dipole estimators discussed in the literature and assess their performances through Monte Carlo simulations. The first method amounts to simple template regression with partial sky data, while the second method is an optimal Wiener filter (or Gibbs sampling) implementation. The main difference between the two methods is that the latter approach takes into account correlations with higher-order CMB temperature fluctuations that arise from nonorthogonal spherical harmonics on an incomplete sky, which for recent CMB data sets (such as Planck) is the dominant source of uncertainty. For an accepted sky fraction of 81% and an angular CMB power spectrum corresponding to the best-fit Planck 2018 ΛCDM model, we find that the uncertainty on the recovered dipole amplitude is about six times smaller for the Wiener filter approach than for the template approach, corresponding to 0.5 and 3 μK, respectively. Similar relative differences are found for the corresponding directional parameters and other sky fractions. We note that the Wiener filter algorithm is generally applicable to any dipole estimation problem on an incomplete sky, as long as a statistical and computationally tractable model is available for the unmasked higher-order fluctuations. The methodology described in this paper forms the numerical basis for the most recent determination of the CMB solar dipole from Planck, as summarized by Planck Collaboration Int. LVII (2020).

Sign in / Sign up

Export Citation Format

Share Document