Entropy maximization constrained by solvent flatness: macromolecular phase extension and refinement
نویسندگان
چکیده
منابع مشابه
Introduction to macromolecular refinement.
The process of refinement is such a large problem in function minimization that even the computers of today cannot perform the calculations to properly fit X-ray diffraction data. Each of the refinement packages currently under development reduces the difficulty of this problem by utilizing a unique combination of targets, assumptions, and optimization methods. This chapter summarizes the basic...
متن کاملAdaptive Contrast Enhancement by Entropy Maximization with a 1-K-1 Constrained Network
This paper uses the Maximum Entropy Principle to construct a 1-K-1 constrained sigmoidal neural network which adaptively adjusts its gain parameters to control the transfer function in order to maximize the entropy measure at the output for image contrast enhancement. We demonstrate how the model works with the standard lena image.
متن کاملRelativistic Equilibrium Distribution by Relative Entropy Maximization
The equilibrium state of a relativistic gas has been calculated based on the maximum entropy principle. Though the relativistic equilibrium state was long believed to be the Jüttner distribution, a number of papers have been published in recent years proposing alternative equilibrium states. However, some of these papers do not pay enough attention to the covariance of distribution functions, r...
متن کاملInverting Monotonic Nonlinearities by Entropy Maximization
This paper proposes a new method for blind inversion of a monotonic nonlinear map applied to a sum of random variables. Such kinds of mixtures of random variables are found in source separation and Wiener system inversion problems, for example. The importance of our proposed method is based on the fact that it permits to decouple the estimation of the nonlinear part (nonlinear compensation) fro...
متن کاملAnnealed Expectation-Maximization by Entropy Projection
We present a new technique of annealing the EM algorithm to allow for its tractable application to fitting models which include graph structures like assignments. The method, which can be generally used to sparsify dependence models, is applied to solve the assignment problem for the shared-resources Gaussian mixture model (e.g. [4], [5],[9]), and is compared to (and contrasted to) the widely u...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Acta Crystallographica Section A Foundations of Crystallography
سال: 1993
ISSN: 0108-7673
DOI: 10.1107/s0108767378098669