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This thesis is concerned with problems in decentralized communication in large networks. Namely, we address the problems of joint rate allocation and transmission of data sources measured at nodes, and of controlling the multiple access of sources to a sha ...
In this paper, we investigate by means of statistical and information-theoretic measures, to what extent sensory-motor coordinated activity can generate and structure information in the sensory channels of a simulated agent interacting with its surrounding ...
We address the problem of reconstructing scalar and vector functions from non-uniform data. The reconstruction problem is formulated as a minimization problem where the cost is a weighted sum of two terms. The first data term is the quadratic measure of go ...
A proposal function determines the random particle support of a particle filter. When this support is distributed close to the true target density, filter's estimation performance increases for a given number of particles. In this paper, a proposal strateg ...
In this paper we address the problem of defining a measure of diversity for a population of individuals whose genome can be subjected to major reorganizations during the evolutionary process. To this end, we introduce a measure of diversity for populations ...
We consider the problem of correlated data gathering by a network with a sink node and a tree communication structure, where the goal is to minimize the total transmission cost of transporting the information collected by the nodes, to the sink node. Two c ...
We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be recon structed at a sink within specified distortion bounds wh ...
An application to antenna optimization of bayesian network density of probability estimators is presented. This technique is very usefull for optimizations where abig number of parameters, multiple solutions and local minima increase the likelihood to conv ...
Recently, we introduced a simple variational bound on mutual information, that resolves some of the difficulties in the application of information theory to machine learning. Here we study a specific application to Gaussian channels. It is well known that ...
We present a method that exploits an information theoretic framework to extract optimal audio features with respect to the video features. A simple measure of mutual information between the resulting audio features and the video ones allows to detect the a ...
