Phase transitions and self-organized criticality in networks of stochastic spiking neurons.

Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold.

A uniform grid structure to speed up example-based photometric stereo.

In this paper, we describe a data structure and an algorithm to accelerate the table lookup step in example-based multiimage photometric stereo. In that step, one must find a pixel of a reference object, of known shape and color, whose appearance under m different illumination fields is similar to that of a given scene pixel. This search reduces to finding the closest match to a given m-vector in a table with a thousand or more m-vectors.

Mutual information content of homologous DNA sequences.

The necessary information to reproduce and keep an organism is codified in acid nucleic molecules. Deepening the knowledge about how the information is stored in these bio-sequences can lead to more efficient methods of comparing genomic sequences. In the present study, we analyzed the quantity of information contained in a DNA sequence that can be useful to identify sequences homologous to it.

The image foresting transform: theory, algorithms, and applications.

The image foresting transform (IFT) is a graph-based approach to the design of image processing operators based on connectivity. It naturally leads to correct and efficient implementations and to a better understanding of how different operators relate to each other. We give here a precise definition of the IFT, and a procedure to compute it-a generalization of Dijkstra's algorithm-with a proof of correctness.