Given a very large, node-weighted, rooted tree on, say, n nodes, if one has only enough space to display a knode summary of the tree, what is the most informative way to draw the tree? We define a type of weighted tree that we call a summary tree of the original tree that results from aggregating nodes of the original tree subject to certain constraints. We suggest that the best choice of which...

this paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (lssvm). two wavelet selection criteria maximum energy to shannon entropy ratio and maximum relative wavelet energy are used and compared to select an appropriate wavelet for feature extraction. the fault diagnosis method co...

this paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (lssvm). two wavelet selection criteria maximum energy to shannon entropy ratio and maximum relative wavelet energy are used and compared to select an appropriate wavelet for feature extraction. the fault diagnosis method co...

An instance crucial to most problems in signal processing is the selection of the order of a presupposed model. Examples are the determination of the putative number of signals present in white Gaussian noise or the number of noise-contaminated sources impinging on a passive sensor array. It is shown that Maximum a Posteriori Bayesian arguments, coupled with Maximum Entropy considerations, offe...

The Maximum Entropy probability density function associated with the testable information on the range and the first and second order moments of the random quantity of interest is derived. The validity of such approach is experimentally demonstrated through comparison between the proposed maximum entropy distribution and the Ushaped distribution. The underlying physical assumptions which must b...

In the propositional setting, the marginal problem is to find a (maximum-entropy) distribution that has some given marginals. We study this problem in a relational setting and make the following contributions. First, we compare two different notions of relational marginals. Second, we show a duality between the resulting relational marginal problems and the maximum likelihood estimation of the ...

During the MaxEnt 2002 workshop in Moscow, Idaho, Tony Vignaux asked again a few simple questions about using Maximum Entropy or Bayesian approaches for the famous Dice problems which have been analyzed many times through this workshop and also in other places. Here, there is another analysis of these problems. I hope that, this paper will answer a few questions of Tony and other participants o...

Maximum Entropy (MaxEnt) models (Jaynes, 1957) are exponential models that implement the intuition that if there is no evidence to favour one alternative solution above another, both alternatives should be equally likely. In order to accomplish this, as much information as possible about the process you want to model must be collected. This information consists of frequencies of events relevant...

The derivation of the maximum entropy distribution of particles in boxes yields two kinds of distributions: a "bell-like" distribution and a long-tail distribution. The first one is obtained when the ratio between particles and boxes is low, and the second one when the ratio is high. The obtained long tail distribution yields correctly the empirical Zipf law, Pareto's 20:80 rule and Benford's l...