This paper considers the problem of interference rejection using sensor array with application to enhance signal reception. In contrast to conventional adaptive beamforming which requires knowledge of the array geometry and array response, we propose a two stage blind signal separation approach to achieve interference rejection. The proposed method is based on the practically viable assumptions...

A method of single channel speech enhancement is proposed by de-noising using stationary wavelet transform. The approach developed herein processes multi-resolution wavelet coefficients individually and then recovery signal is reconstructed. The time invariant characteristics of stationary wavelet transform is particularly useful in speech de-noising. Experimental results show that the proposed...

Real-world processes generally produce observable outputs, which can be characterized as signals. The signals can be discrete in nature (e.g., characters from a finite alphabet, quantized vectors from a codebook), or continuous in nature (e.g., speech samples, temperature measurements, music). The signal source can be stationary (i.e., its statistical properties do not vary with time), or non-s...

The problem of joint estimation of power spectrum and modulation from realizations of frequency modulated stationary wideband signals is considered. The study is motivated by some specific signal classes from which departures to stationarity can carry relevant information and has to be estimated. The estimation procedure is based upon explicit modeling of the signal as a wideband stationary Gau...

Most of recent and important algorithms in signal processing (for blind identification or separation, etc) are based on higher order statistics (HOS). And most of them use a criteria based on the fourth order statistics (moment or cumulant). The problem of using HOS consists on the estimation of the statistics. In the literature, three different estimators of the fourth order cumulant were used...

The noise in reconstructed slices of X-ray Computed Tomography (CT) is of unknown distribution, non-stationary, oriented and difficult to distinguish from main structural information. This requires the development of special post-processing methods based on the local statistical evaluation of the noise component. This paper presents an adaptive method of reducing noise in CT images employing th...

One of the major concerns in deploying speech recognition applications is the lack of robustness of the technology. One key aspect is the sensitivity to stationary or non-stationary background noise. Many approaches to noise robust speech recognition have been proposed before. Some modify the front-end signal processing of the recogniser while others work on the back-end, i.e. modelling and dec...

A method for applying Kalman filtering to speechsignals corrupted by colored noise is presented. Both speech and colored noise are modeled as autoregressive (AR) processesusing speechand silence regions determined by an automatic end-point detector. Due to the non-stationary nature of the speech signal, non-stationary Kalman filter is used. Experiments indicate that non-stationary Kalman filter...

Revealing the functional meaning of EEG and MEG signals’ nonstationarity and metastability is one of the major topics in current brain research. Indeed, the explicit quasi-stationary phenomena in the activity of large neuronal populations are still largely unknown. However, the fast dynamics of quasi-stationary episodes in EEG/MEG signal, together with rapid transitive periods between them, fit...