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About the choice of the variable to unassign in a decision repair algorithm

Cédric Pralet, Gérard Verfaillie (2010)

RAIRO - Operations Research

The decision repair algorithm (Jussien and Lhomme, Artificial Intelligence139 (2002) 21–45), which has been designed to solve constraint satisfaction problems (CSP), can be seen, either (i) as an extension of the classical depth first tree search algorithm with the introduction of a free choice of the variable to which to backtrack in case of inconsistency, or (ii) as a local search algorithm in the space of the partial consistent variable assignments. or (iii) as a hybridisation between local...

About the decision of reachability for register machines

Véronique Cortier (2002)

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

We study the decidability of the following problem: given p affine functions f 1 , ... , f p over ℕ k and two vectors v 1 , v 2 ∈ ℕ k , is v 2 reachable from v 1 by successive iterations of f 1 , ... , f p (in this given order)? We show that this question is decidable for p = 1 , 2 and undecidable for some fixed p .

About the decision of reachability for register machines

Véronique Cortier (2010)

RAIRO - Theoretical Informatics and Applications

We study the decidability of the following problem: given p affine functions ƒ1,...,ƒp over ℕ k and two vectors v 1 , v 2 ∈ ℕ k , is v2 reachable from v1 by successive iterations of ƒ1,...,ƒp (in this given order)? We show that this question is decidable for p = 1, 2 and undecidable for some fixed p.

About the maximum information and maximum likelihood principles

Igor Vajda, Jiří Grim (1998)

Kybernetika

Neural networks with radial basis functions are considered, and the Shannon information in their output concerning input. The role of information- preserving input transformations is discussed when the network is specified by the maximum information principle and by the maximum likelihood principle. A transformation is found which simplifies the input structure in the sense that it minimizes the entropy in the class of all information-preserving transformations. Such transformation need not be unique...

Abstract Reduction Systems and Idea of Knuth-Bendix Completion Algorithm

Grzegorz Bancerek (2014)

Formalized Mathematics

Educational content for abstract reduction systems concerning reduction, convertibility, normal forms, divergence and convergence, Church- Rosser property, term rewriting systems, and the idea of the Knuth-Bendix Completion Algorithm. The theory is based on [1].

Acceleration of Le Bail fitting method on parallel platforms

Mařík, Ondřej, Šimeček, Ivan (2015)

Programs and Algorithms of Numerical Mathematics

Le Bail fitting method is procedure used in the applied crystallography mainly during the crystal structure determination. As in many other applications, there is a need for a great performance and short execution time. In this paper, we describe utilization of parallel computing for mathematical operations used in Le Bail fitting. We present an algorithm implementing this method with highlighted possible approaches to its aforementioned parallelization. Then, we propose a sample parallel version...

Access structures for finding characteristic-dependent linear rank inequalities

Victor Peña-Macias (2023)

Kybernetika

Determining information ratios of access structures is an important problem in secret sharing. Information inequalities and linear rank inequalities play an important role for proving bounds on these ratios. Characteristic-dependent linear rank inequalities are rank inequalities which are true over vector spaces with specific field characteristic. In this paper, using ideas of secret sharing, we show a theorem that produces characteristic-dependent linear rank inequalities. These inequalities are...

Accurate and online-efficient evaluation of the a posteriori error bound in the reduced basis method

Fabien Casenave, Alexandre Ern, Tony Lelièvre (2014)

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

The reduced basis method is a model reduction technique yielding substantial savings of computational time when a solution to a parametrized equation has to be computed for many values of the parameter. Certification of the approximation is possible by means of an a posteriori error bound. Under appropriate assumptions, this error bound is computed with an algorithm of complexity independent of the size of the full problem. In practice, the evaluation of the error bound can become very sensitive...

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