We consider a differential method of maximum entropy that is based on the linearity of Fourier transform and involves reconstruction of images from the differences of the visibility function. The efficiency of the method is demonstrated with respect to the recovery of source images with bright components against the background of a sufficiently weak extended base. The simulation results are giv...

We tackle the inverse problem of reconstructing an unknown finite measure μ from a noisy observation of a generalized moment of μ defined as the integral of a continuous and bounded operator Φ with respect to μ . When only a quadratic approximation Φm of the operator is known, we introduce the L2 approximate maximum entropy solution as a minimizer of a convex functional subject to a sequence of...

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...

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...

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, ...

Based on the minimization of the Lagrange formula, which is composed of two kinds of information measure, the maximum entropy method (MEM) is derived for diffractive imaging contaminated by quantum noise. This gives a suitable object corresponding to the maximum entropy principle with an iterative procedure. The MEM-based iterative phase retrieval algorithm with the initial process of the hybri...

We propose a method to calculate the QCD level density directly from the thermodynamic quantities obtained by lattice QCD simulations with the use of the maximum entropy method (MEM). Understanding QCD thermodynamics from QCD spectral properties has its own importance. Also it has a close connection to phenomenological analyses of the lattice data as well as experimental data on the basis of ha...

We tackle the inverse problem of reconstructing an unknown finite measure μ from a noisy observation of a generalized moment of μ defined as the integral of a continuous and bounded operator Φ with respect to μ . When only a quadratic approximation Φm of the operator is known, we introduce the L2 approximate maximum entropy solution as a minimizer of a convex functional subject to a sequence of...

In Monte Carlo simulations of lattice field theory with a θ term, one confronts the complex weight problem, or the sign problem. This is circumvented by performing the Fourier transform of the topological charge distribution P (Q). This procedure, however, still causes the flattening phenomenon of the free energy, which prevents one from studying the phase structure. In order to work at this is...

In this paper, at first we derive a family of maximum Tsallis entropy distributions under optional side conditions on the mean income and the Gini index. Furthermore, corresponding with these distributions a family of Lorenz curves compatible with the optional side conditions is generated. Meanwhile, we show that our results reduce to Shannon entropy as $beta$ tends to one. Finally, by using ac...