A great challenge in neurophysiology is to asses non-invasively the physiological changes occurring in different parts of the brain. These activation can be modeled and measured often as neuronal brain source signals that indicate the function or malfunction of various physiological subsystems. To extract the relevant information for diagnosis and therapy, expert knowledge is required not only ...

In OFDM communications, the loss of orthogonality due to carrier offset must be compensated before DFT-based demodulation can be performed. In this paper, we present a high accuracy blind carrier offset estimation algorithm and a blind channel equalizer which exploit the intrinsic structure information of OFDM signals. The latter method allows the receiver to perform coherent demodulation in ch...

Although there are several risk factors for glaucoma, elevated intraocular pressure (IOP) remains the major risk factor. Palpation is one of the oldest, simplest, and least expensive methods for approximate IOP assessment. Researchers believe that blind individuals may possess a more acutely developed sense of touch, which has already proved to be beneficial in clinical breast examination to de...

This paper addresses the estimation of fuzzy Gaussian distribution mixture with applications to unsupervised statistical fuzzy image segmentation. In a general way, the fuzzy approach enriches the current statistical models by adding a fuzzy class, which has several interpretations in signal processing. One such interpretation in image segmentation is the simultaneous appearance of several them...

This paper introduces a blind method based on Bayesian maximum a posteriori estimation theory for restoring images corrupted by noise and blurred by one or more unknown point spread functions. Image and blur prior information is expressed in the form of parametric generalized Gauss Markov random field models. A method for estimating the GGMRF neighborhood influence parameters is presented, alon...

| In this paper we present an adaptive blind receiver for asynchronous direct sequence code division multiple access (DS-CDMA) communication over multipath channels. The algorithm can handle both multiuser interference (MUI) and intersymbol interference (ISI) by the use of a twofold spreading together with some spatial over-sampling. It is based on a blind virtual channel identiication using th...

In this paper, the blind channel identification problem is formulated in a stochastic state space framework. Starting from a state space model we present a preprocessing step based on two orthogonal subspace projections. Using these orthogonal projections, we derive an algorithm for blind channel estimation which is insensitive to the spatial color of the noise. The performance of this new algo...

This paper presents the convergence analysis of a prediction based blind equalizer for IIR channels. Predictor parameters are estimated by using the recursive least squares algorithm. It is shown that the prediction error converges almost surely (a.s.) toward a scalar multiple of the unknown input symbol sequence. It is also proved that the convergence rate of the parameter estimation error is ...

The aim of this paper is to provide performance analysis of a deterministic method proposed recently for blind identication of linear time-invariant channels, in the presence of additive noise, for block transmission systems using redundant precoding. Robustness of the blind estimation method is also analyzed in the presence of slow channel variations arising due to Doppler shifts or due to pha...

A blind single-image super resolution method is proposed to enhance the spatial resolution of the image with defocus blur. Firstly, according to the low resolution imaging model, a framework of blind singleimage super resolution reconstruction is presented. Secondly, utilizing Wiener filtering algorithm, the errorparameter curve of the defocus blurred image was generated, through which the defo...