Variational viewpoint of the quadratic Markov measure field models: theory and algorithms.

We present a framework for image segmentation based on quadratic programming, i.e., by minimization of a quadratic regularized energy linearly constrained.

Morphology-based hypothesis testing in discrete random fields: a non-parametric method to address the multiple-comparison problem in neuroimaging.

A new method for detecting activations in random fields, which may be useful for addressing the issue of multiple comparisons in neuroimaging, is presented. This method is based on some constructs of mathematical morphology - specifically, morphological erosions and dilations - that enable the detection of active regions in random fields possessing moderate activation levels and relatively large spatial extension, which may not be detected by the standard methods that control the family-wise error rate. The method presented here permits an appropriate control of the false positive errors, without having to adjust any threshold values, other than the significance level.

High-performance multimedia encryption system based on chaos.

Current chaotic encryption systems in the literature do not fulfill security and performance demands for real-time multimedia communications. To satisfy these demands, we propose a generalized symmetric cryptosystem based on N independently iterated chaotic maps (N-map array) periodically perturbed with a three-level perturbation scheme and a double feedback (global and local) to increase the system's robustness to attacks. The first- and second-level perturbations make cryptosystem extremely sensitive to changes in the plaintext data since the system's output itself (ciphertext global feedback) is used in the perturbation process.

Exploratory EEG data analysis for psychophysiological experiments.

A method for the exploratory analysis of electroencephalographic (EEG) data for neurophysiological experiments is presented. It is based on a time-frequency decomposition of the EEG time series, which is measured by several electrodes in the scalp surface, and includes the computation of a statistic that measures the deviations of the log-power with respect to the pre-stimulus average; the computation of a significance index for these deviations; a new type of display (the time-frequency-topography plot) for the visualization of these indices, and the segmentation of the time-frequency plane into regions with uniform activation patterns. As a particular example, an experiment to study EEG changes during figure and word categorization is analyzed in detail.