Protein Structure Comparison by Mean Field Approximation

Estimation of Software Reliability by Sequential Testing with Simulated Annealing of Mean Field Approximation

Various problems of combinatorial optimization and permutation can be solved with neural network optimization. The problem of estimating the software reliability can be solved with the optimization of failed components to its minimum value. Various solutions of the problem of estimating the software reliability have been given. These solutions are exact and heuristic, but all the exact approach...

Protein Structure Alignment using Mean Field Annealing

Unraveling functional and ancestral relationships between proteins as well as structure prediction procedures require powerful protein alignment methods. This paper describes the use of fuzzy alignments when matching protein structures. The method use mean-field annealing optimization of fuzzy alignment variables, based on a cost expressed in terms of distances between aligned atoms and of gaps...

Mean Field Approximation for Fields of Experts

Information Geometry of Mean-Field Approximation

I present a general theory of mean-field approximation based on information geometry and applicable not only to Boltzmann machines but also to wider classes of statistical models. Using perturbation expansion of the Kullback divergence (or Plefka expansion in statistical physics), a formulation of mean-field approximation of general orders is derived. It includes in a natural way the "naive" me...

Mean Field Approximation in Conformation Dynamics

We propose a new approach to the transfer operator based analysis of the conformation dynamics of molecules. It is based on a statistical independence ansatz for the eigenfunctions of the operator related to a partitioning into subsystems. Numerical tests performed on small systems show excellent qualitative agreement between mean field and exact model, at greatly reduced computational cost.