Does the maximum entropy method improve sensitivity?

The Maximum Entropy on the Mean Method, Noise and Sensitivity

In this paper we address the problem of building convenient criteria to solve linear and noisy inverse problems of the form y = Ax + n. Our approach is based on the speci cation of constraints on the solution x through its belonging to a given convex set C. The solution is chosen as the mean of the distribution which is the closest to a reference measure on C with respect to the Kullback diverg...

Maximum Entropy Method for Composition Vector Method

The Maximum Entropy Method for Lifetime Distributions

An approach to produce a model for the data generating distribution is the well-known maximum entropy method. In this approach, the partial knowledge about the data generating distribution is formulated in terms of a set of information constraints, usually moment constraints, and the inference is based on the model that maximizes Shannon’s entropy under these constraints. In this paper we inves...

Deconvolution by the Multiscale Maximum Entropy Method

In 1994, to overcome the diiculties encountered by the Maximum Entropy Method (MEM) to restore images containing both high and low frequencies, Bontekoe et al. introduced the Pyramid Maximum Entropy Deconvolution. However, this method presents several drawbacks such as parameters estimation (model, alpha). Following these ideas, we propose the Multiscale Maximum Entropy Method which is based on...

The Maximum Entropy Method 1 ( Invited paper )

We have heard so far at this meeting from the practical-minded men of radio astronomy. Faced with the problem: ‘my map has sidelobes and noise on it’, they promptly reach for the nearest available weapons — ‘cleaners, polishers and kneaders’. All these use varying amounts of subjective human judgement, as for example in ‘window cleaning’. The ideas of the maximum entropy method are intriguing, ...