In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI) and can be reduced significantly by applying a blind adaptive deconvolution process (blind adaptive equalizer) on the distorted received symbols. But, since the entire blind deco...

BACKGROUND An unknown input function can be determined by deconvolution using the systemic bolus input function (r) determined using an experimental input of duration ranging from a few seconds to many minutes. The quantitative relation between the duration of the input and the accuracy of r is unknown. Although a large number of deconvolution procedures have been described, these routines are ...

Colour deconvolution is a method used in diagnostic brightfield microscopy to transform colour images of multiple stained biological samples into images representing the stain concentrations. It is applied by decomposing the absorbance values of stain mixtures into absorbance values of single stains. The method assumes a linear relation between stain concentration and absorbance, which is only ...

The deconvolution kernel density estimator is a popular technique for solving the deconvolution problem, where the goal is to estimate a density from a sample of contaminated observations. Although this estimator is optimal, it suffers from two major drawbacks: it converges at very slow rates (inherent to the deconvolution problem) and can only be calculated when the density of the errors is co...

In this paper we present a general framework of the state space approach for blind deconvolution. First, we review the current state of the art of blind deconvolution using statespace models, then give a new insight into blind deconvolution in the state-space framework. The cost functions for blind deconvolution are discussed and adaptive learning algorithms for updating external parameters are...

Introduction With the advances in fast MR imaging techniques, it is possible to monitor the traversal of a MR contrast agent within tissues at short time intervals (of the order of a few seconds or less), thereby allowing the possibility to study blood flow at the tissue level. Dynamic contrastenhanced MRI (DCE MRI) is emerging as a promising approach for in vivo assessment of tissue microcircu...

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to g...

We propose a probabilistic model for the Independent Vector Analysis approach to blind deconvolution and derive an asymptotic Newton method to estimate the model by Maximum Likelihood.

In this paper the multiframe blind deconvolution method 1] for the identiication and correction of turbulence-induced phase aberrations in a ground-based telescope is extended to include the gains, backgrounds, and biases inherent in many charge-coupled device (CCD) cameras. In addition, an application of this method to real telescope data is described.

Generalized Linnik processes and associated logarithmic diffusion equations can be constructed by appropriate Bochner randomization of the time variable in Brownian motion and the related heat conduction equation. Remarkably, over a large but finite frequency range, generalized Linnik characteristic functions can exhibit almost Gaussian behavior near the origin, while behaving like low exponent...