This paper communicates a novel method of Wiener filtering signals from scientific instruments to reduce their noise content. The main prerequisite for the applicability of this technique is that the pure (i.e. noiseless) signal is reproducible, a condition that is satisfied by a wide range of experimental measurements. The benefits of this Wiener filter design approach are its simplicity, gene...

The presence of non-linear effects in adaptive filtering was observed previously in a wide sense stationary equalization scenario with narrowband interference. The influence of a variety of parameters on the magnitude of such non-linear effects was also investigated. While the adaptive filter appears to exhibit behavior that one would expect in a wide sense stationary scenario, we show here tha...

In wireless OFDM systems, the time-varying channel is often estimated by a Wiener filter-type MMSE estimator based on pilot symbols. Such an estimator, however, requires statistical prior knowledge that is not easily obtained. Here, we propose adaptive Wiener filters for channel estimation that do not require statistical prior knowledge. We also calculate the performance limits of finite-length...

In an adaptive generalized sidelobe canceler interference signals are canceled when the reference inputs, or auxiliary beams, contain information about those interference signals while not containing information about the mainlobe signal of interest. Assuming a wide sense stationary scenario, the behavior and performance of this adaptive system approach the behavior and performance of the corre...

In this study by using noise-free signal estimation the reduction of noise in the image is being proposed. The dyadic stationary wavelet transform is used for both the wiener filter and in estimating the noise free signal. Finding a suitable filter bank and choosing other parameters of the wiener filter with respect to obtained signalto-noise ratio (SNR) is our goal. Testing was being performed...

The non-linear effects that have been observed in adaptive filtering scenarios arc explained from the point of view of the structure that underlies the desired data. While the model structure used by the conventional adaptive filter is a linear combination of lapped-dclay line signals, that adaptive filter model does not generally correspond to the structure that best describes the desired data...

The multistage Wiener filter (MWF) outperforms the full rank Wiener filter in low sample support environments. However, the MWF adaptive process should be stopped at an optimum stage to get the best performance. There are two methods to stop the MWF adaptive process. One method is to calculate until the final full-stage, and the second method is to terminate at r-stage less than full-stage. The...

This paper proposes an adaptive Wiener filtering method for speech enhancement. This method depends on the adaptation of the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance. It is implemented in the time M.A. Abd El-Fattah · M.I. Dessouky · A.M. Abbas · S.M. Diab · S.M. El-Rabaie · F.E. Abd El-samie (B) Department of El...

In this paper we introduce the generalized feedforward filter, a new class of adaptive filters that combine attractive properties of Finite Impulse Response (FIR) filters with some of the power of Infinite Impulse Response (IIR) filters. A particular case, the adaptive gamma filter, generalizes Widrow’s adaptive linear combiner (adaline) to an infinite impulse response filter. Yet, the stabilit...

We propose a signal-adaptive robust time-varying Wiener filter for nonstationary signal estimation/enhancement. This filter uses projections onto local cosine subspaces and a novel “best subspace” algorithm. It allows efficient on-line operation including stable online estimation of design parameters. A statistical analysis is provided, and a speech enhancement example is considered.