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Direct adaptive control of unknown nonlinear systems using a new neuro-fuzzy method together with a novel approach of parameter hopping

Dimitris Theodoridis, Yiannis Boutalis, Manolis Christodoulou (2009)

Kybernetika

The direct adaptive regulation for affine in the control nonlinear dynamical systems possessing unknown nonlinearities, is considered in this paper. The method is based on a new Neuro-Fuzzy Dynamical System definition, which uses the concept of Fuzzy Dynamical Systems (FDS) operating in conjunction with High Order Neural Network Functions (F-HONNFs). Since the plant is considered unknown, we first propose its approximation by a special form of a fuzzy dynamical system (FDS) and in the sequel the...

Directed forests with application to algorithms related to Markov chains

Piotr Pokarowski (1999)

Applicationes Mathematicae

This paper is devoted to computational problems related to Markov chains (MC) on a finite state space. We present formulas and bounds for characteristics of MCs using directed forest expansions given by the Matrix Tree Theorem. These results are applied to analysis of direct methods for solving systems of linear equations, aggregation algorithms for nearly completely decomposable MCs and the Markov chain Monte Carlo procedures.

Directive words of episturmian words : equivalences and normalization

Amy Glen, Florence Levé, Gwénaël Richomme (2009)

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

Episturmian morphisms constitute a powerful tool to study episturmian words. Indeed, any episturmian word can be infinitely decomposed over the set of pure episturmian morphisms. Thus, an episturmian word can be defined by one of its morphic decompositions or, equivalently, by a certain directive word. Here we characterize pairs of words directing the same episturmian word. We also propose a way to uniquely define any episturmian word through a normalization of its directive words. As a consequence...

Directive words of episturmian words: equivalences and normalization

Amy Glen, Florence Levé, Gwénaël Richomme (2008)

RAIRO - Theoretical Informatics and Applications

Episturmian morphisms constitute a powerful tool to study episturmian words. Indeed, any episturmian word can be infinitely decomposed over the set of pure episturmian morphisms. Thus, an episturmian word can be defined by one of its morphic decompositions or, equivalently, by a certain directive word. Here we characterize pairs of words directing the same episturmian word. We also propose a way to uniquely define any episturmian word through a normalization of its directive words. As a consequence...

Discrete approximation of the Mumford-Shah functional in dimension two

Antonin Chambolle, Gianni Dal Maso (2010)

ESAIM: Mathematical Modelling and Numerical Analysis

The Mumford-Shah functional, introduced to study image segmentation problems, is approximated in the sense of vergence by a sequence of integral functionals defined on piecewise affine functions.

Discrete planes, ℤ 2 -actions, Jacobi-Perron algorithm and substitutions

Pierre Arnoux, Valérie Berthé, Shunji Ito (2002)

Annales de l’institut Fourier

We introduce two-dimensional substitutions generating two-dimensional sequences related to discrete approximations of irrational planes. These two-dimensional substitutions are produced by the classical Jacobi-Perron continued fraction algorithm, by the way of induction of a ℤ 2 -action by rotations on the circle. This gives a new geometric interpretation of the Jacobi-Perron algorithm, as a map operating on the parameter space of ℤ 2 -actions by rotations.

Discrete-time symmetric polynomial equations with complex coefficients

Didier Henrion, Jan Ježek, Michael Šebek (2002)

Kybernetika

Discrete-time symmetric polynomial equations with complex coefficients are studied in the scalar and matrix case. New theoretical results are derived and several algorithms are proposed and evaluated. Polynomial reduction algorithms are first described to study theoretical properties of the equations. Sylvester matrix algorithms are then developed to solve numerically the equations. The algorithms are implemented in the Polynomial Toolbox for Matlab.

Discriminating between causal structures in Bayesian Networks given partial observations

Philipp Moritz, Jörg Reichardt, Nihat Ay (2014)

Kybernetika

Given a fixed dependency graph G that describes a Bayesian network of binary variables X 1 , ⋯ , X n , our main result is a tight bound on the mutual information I c ( Y 1 , ⋯ , Y k ) = ∑ j = 1 k H ( Y j ) / c - H ( Y 1 , ⋯ , Y k ) of an observed subset Y 1 , ⋯ , Y k of the variables X 1 , ⋯ , X n . Our bound depends on certain quantities that can be computed from the connective structure of the nodes in G . Thus it allows to discriminate between different dependency graphs for a probability distribution, as we show from numerical experiments.

Currently displaying 121 – 140 of 193