Revisiting Identification Concepts in Bayesian Analysis

Revisiting Bayesian blind deconvolution

Blind deconvolution involves the estimation of a sharp signal or image given only a blurry observation. Because this problem is fundamentally ill-posed, strong priors on both the sharp image and blur kernel are required to regularize the solution space. While this naturally leads to a standard MAP estimation framework, performance is compromised by unknown trade-off parameter settings, optimiza...

A Bayesian system identification analysis

A Bayesian system identification technique was used to determine which image characteristics predict where people fixate when viewing natural images. More specifically an estimate was derived for the mapping between image characteristics at a given location and the probability that this location was fixated. Using a large database of eye fixations to natural images, we determined the most proba...

Bayesian Prediction in Spatial Data Analysis

Revisiting concepts on sleep-wake timing

Forty years ago, Moruzzi (1972) presented in a seminal article an overview of knowledge accumulated by then on neural mechanisms underlying sleep, wakefulness and their alternation. We here wish to revisit, in the light of modern knowledge, sections of the last part of this article, as well as a review written by Berlucchi (1970) to which Moruzzi (1972) refers. These texts are especially inspir...

Basic Concepts of Bayesian Programming

The purpose of this chapter is to introduce gently the basics concepts of Bayesian Programming. After a short formal introduction of Bayesian Programming, we present these concepts using three simple experiments with the mini mobile robot Khepera. These three instances have been selected among the numerous experiments done with this robots for their simplicity and didactic quality. A more exten...