One of the main objectives within the adaptive signal processing is the noise suppression, i.e. the detection of information bearing signal in noise. Adaptive filter application ANC (Adaptive Noise Cancellation) using adaptive Filter algorithm is an important basis for signal processing. The device automatically filters out the components of the signal which are not related to the orignal signa...

This paper describes the architecture of a microwave radar system intended for imaging concealed objects under clothing as a subject walks through the inspection area. The system uses the principle of inverse aperture which is achieved by a person’s movement past a stationary microwave sensor array. In the system, the vertical resolution is achieved by arranging microwave sensors vertically whi...

Stationary solutions to a Fokker-Planck equation corresponding to a noisy logistic equation with correlated Gaussian white noises are constructed. Stationary distributions exist even if the corresponding deterministic system displays an unlimited growth. Positive correlations between the noises can lead to a minimum of the variance of the process and to the stochastic resonance if the system is...

We study compressed sensing (CS) signal reconstruction problems where an input signal is measured via matrix multiplication under additive white Gaussian noise. Our signals are assumed to be stationary and ergodic, but the input statistics are unknown; the goal is to provide reconstruction algorithms that are universal to the input statistics. We present a novel algorithm that combines: (i) the...

In this paper, we present a novel approach for real-time multichannel speech enhancement in environments of non-stationary noise and time-varying acoustical transfer functions (ATFs). The proposed system integrates adaptive beamforming, ATF identification, soft signal detection, and multichannel postfiltering. The noise canceller branch of the beamformer and the ATF identification are adaptivel...

Analysis of long-term EEG signals needs that it be segmented into pseudo stationary epochs. That work is done by regarding to statistical characteristics of a signal such as amplitude and frequency. Time series measured in real world is frequently non-stationary and to extract important information from the measured time series it is significant to utilize a filter or smoother as a pre-processi...

We consider the blind separation of an instantaneous mixture of non stationary source signals, possibly normally distributed. The asymptotic Cramér-Rao bound is exhibited in the case of known source distributions: it reveals how non stationarity and non Gaussianity jointly governs the achievable performance via an index of non stationarity and an index of non Gaussianity.

| In this paper, we investigate the noise suppression performance of a novel adaptive lter based on sub-space methods. In contrast to conventional subspace lters, this approach requires no eigenvalue or singular value decomposition. Therefore, our adaptive subspace lter can be implemented for real-time operation using general purpose digital signal processors. In addition, only the noisy signal...