This paper investigates the performance of the T-distributions as compared to other well known time-frequency distributions in a recently proposed blind source separation algorithm based on timefrequency analysis. In this study we considered linear FM signals (chirps), non-linear FM signals, and doppler signals. Keyword:Blind Source Separation; Time-frequency representation; Doppler signal; Lin...

A neural architecture based on linear predictability is used to separate linear mixtures of signals. The architecture is divided in two parameterers groups, one modeling the linear mixture of signals and the other computing the linear predictions of the reconstructed signals. The network weights correspond to the mixing matrices and coefficients of the linear predictions, while the values compu...

localization of sources in patients with focal seizure has recently attracted many attentions. in the severe cases of focal seizure, there is a possibility of doing neurosurgery operation to remove the defected tissue. the prosperity of this heavy operation completely depends on the accuracy of source localization. to increase this accuracy, this paper presents a new weighted beamforming method...

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...

Chaos based communications have drawn increasing attention over the past years. Chaotic signals are derived from non-linear dynamic systems. They are aperiodic, broadband and deterministic signals that appear random in the time domain. Because of these properties, chaotic signals have been proposed to generate spreading sequences for wide-band secure communication recently. Like conventional DS...