iener theory, formulated by Norbert Wiener, forms the foundation of data-dependent linear least square error filters. Wiener filters play a central role in a wide range of applications such as linear prediction, echo cancellation, signal restoration, channel equalisation and system identification. The coefficients of a Wiener filter are calculated to minimise the average squared distance betwee...

Form the past several decades' noise cancellation in speech signal gains researchers' attention. Several techniques were developed for noise cancellation among them optimal wiener filter can be the one of the most fundamental approach for noise cancellation. Later on adaptive filter was introduced to attain better performance. This paper shows the capacity of wiener filter and adaptiv...

In this paper, a real-time denoising filter based on modelling of stable hybrid models is presented. Thehybrid models are composed of the shearlet filter and the adaptive Wiener filter in different forms.The optimization of various models is accomplished by the genetic algorithm. Next, regarding thesignificant relationship between Optimal models and input images, changing the structure of Optim...

In this work, we consider the adaptive Wiener filtering of noisy images and image sequences. We begin by using an adaptive weighted averaging (AWA) approach to estimate the second-order statistics required by the Wiener filter. Experimentally, the resulting Wiener filter is improved by about 1dB in the sense of peak-to-peak SNR (PSNR). Also, the subjective improvement is significant in that the...

In this paper a novel transversal split filter configuration is proposed and the split optimum Wiener filter is introduced, as well as the symmetric and antisymmetric linear phase Wiener filter. The approach consists of combining the idea of split filtering with a linearlyconstrained optimization scheme. Then, the continuously split procedure is introduced and the multi-split adaptive filter is...

In a number of adaptive filtering applications, non-Wiener effects have been observed for the (normalized) leastmean-square algorithm. These effects can lead to performance improvements over the fixed Wiener filter with the same model structure, and are characterized by dynamic behavior of the adaptive filter weights. Here we investigate whether such non-Wiener effects can also occur in the rec...

An innovative space-time adaptive preprocessing algorithm based on a low complexity multistage nested Wiener filter is introduced. A closed form expression for the Wiener-Hopf filter weights is developed using the multistage nested Wiener falter parameters. It is demonstrated that this algorithm is capable of suppressing both wideband and narrowband jammers while maintaining low complexity.

This paper investigates the nonlinear effects of the LeastMean Square (LMS) adaptive predictor. Traditional analysis of the adaptive filter ignores the statistical dependence among successive tap-input vectors and bounds the performance of the adaptive filter by that of the finite-length Wiener filter. It is shown that the nonlinear effects make it possible for an adaptive transversal predictio...

Robust Implementations of the Multistage Wiener Filter By John David Hiemstra The research in this dissertation addresses reduced rank adaptive signal processing, with specific emphasis on the multistage Wiener filter (MWF). The MWF is a generalization of the classical Wiener filter that performs a stage-by-stage decomposition based on orthogonal projections. Truncation of this decomposition pr...

Common motion compensated hybrid video coding standards such as H.263, MPEG-1, MPEG-2, MPEG-4 are based on a fractional-pel displacement vector (DV) resolution of 1/2-pel. Recent approaches like MPEG-4 (ACE-profile) and H.26L use higher DV resolutions of 1/4-pel and 1/8-pel. In order to estimate and compensate fractional-pel displacements, the image signal has to be interpolated. Especially for...