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Global stability analysis and control of leptospirosis

Kazeem Oare Okosun, M. Mukamuri, Daniel Oluwole Makinde (2016)

Open Mathematics

The aim of this paper is to investigate the effectiveness and cost-effectiveness of leptospirosis control measures, preventive vaccination and treatment of infective humans that may curtail the disease transmission. For this, a mathematical model for the transmission dynamics of the disease that includes preventive, vaccination, treatment of infective vectors and humans control measures are considered. Firstly, the constant control parameters’ case is analyzed, also calculate the basic reproduction...

Global stability of linearizing control with a new robust nonlinear observer of the induction motor

Mohammed Chenafa, Abdellah Mansouri, Abderrahmane Bouhenna, Eric Etien, Abdelkader Belaidi, Mouloud Denai (2005)

International Journal of Applied Mathematics and Computer Science

This paper mainly deals with the design of an advanced control law with an observer for a special class of nonlinear systems. We design an observer with a gain as a function of speed. We study the solution to the output feedback torque and rotor flux-tracking problem for an induction motor model given in the natural frame. We propose a new robust nonlinear observer and prove the global stability of the interlaced controller-observer system. The control algorithm is studied through simulations and...

Global synchronization of chaotic Lur’e systems via replacing variables control

Xiaofeng Wu, Yi Zhao, Muhong Wang (2008)

Kybernetika

Finding sufficient criteria for synchronization of master-slave chaotic systems by replacing variables control has been an open problem in the field of chaos control. This paper presents some recent works on the subject, with emphasis on chaos synchronization of both identical and parametrically mismatched Lur’e systems by replacing variables control. The synchronization schemes are formally constructed and two classes of sufficient criteria for global synchronization, linear matrix inequality criterion...

Globality in semisimple Lie groups

Karl-Hermann Neeb (1990)

Annales de l'institut Fourier

In the first section of this paper we give a characterization of those closed convex cones (wedges) W in the Lie algebra s l ( 2 , R ) n which are invariant under the maximal compact subgroup of the adjoint group and which are controllable in the associated simply connected Lie group S l ( 2 , R ) n ∼ , i.e., for which the subsemigroup S = ( exp W ) generated by the exponential image of W agrees with the whole group G (Theorem 13). In Section 2 we develop some algebraic tools concerning real root decompositions with respect to compactly...

Globally uniformly ultimately bounded observer design for a class of nonlinear systems with sampled and delayed measurements

Daoyuan Zhang, Yanjun Shen, Xiao Hua Xia (2016)

Kybernetika

In this paper, we consider two kinds of sampled-data observer design for a class of nonlinear systems. The system output is sampled and transmitted under two kinds of truncations. Firstly, we present definitions of the truncations and the globally uniformly ultimately bounded observer, respectively. Then, two kinds of observers are proposed by using the delayed measurements with these two truncations, respectively. The observers are hybrid in essence. For the first kind of observers, by constructing...

Goodman-Kruskal Measure of Association for Fuzzy-Categorized Variables

S. M. Taheri, Gholamreza Hesamian (2011)

Kybernetika

The Goodman-Kruskal measure, which is a well-known measure of dependence for contingency tables, is generalized to the case when the variables of interest are categorized by linguistic terms rather than crisp sets. In addition, to test the hypothesis of independence in such contingency tables, a novel method of decision making is developed based on a concept of fuzzy p -value. The applicability of the proposed approach is explained using a numerical example.

Gradient observability for diffusion systems

El Hassane Zerrik, Hamid Bourray (2003)

International Journal of Applied Mathematics and Computer Science

The aim of this paper is to study regional gradient observability for a diffusion system and the reconstruction of the state gradient without the knowledge of the state. First, we give definitions and characterizations of these new concepts and establish necessary conditions for the sensor structure in order to obtain regional gradient observability. We also explore an approach which allows for a regional gradient reconstruction. The developed method is original and leads to a numerical algorithm...

Graphical model selection for a particular class of continuous-time processes

Mattia Zorzi (2019)

Kybernetika

Graphical models provide an undirected graph representation of relations between the components of a random vector. In the Gaussian case such an undirected graph is used to describe conditional independence relations among such components. In this paper, we consider a continuous-time Gaussian model which is accessible to observations only at time T . We introduce the concept of infinitesimal conditional independence for such a model. Then, we address the corresponding graphical model selection problem,...

Graphics card as a cheap supercomputer

Přikryl, Jan (2013)

Programs and Algorithms of Numerical Mathematics

The current powerful graphics cards, providing stunning real-time visual effects for computer-based entertainment, have to accommodate powerful hardware components that are able to deliver the photo-realistic simulation to the end-user. Given the vast computing power of the graphics hardware, its producers very often offer a programming interface that makes it possible to use the computational resources of the graphics processors (GPU) to more general purposes. This step gave birth to the so-called...

Graphics processing units in acceleration of bandwidth selection for kernel density estimation

Witold Andrzejewski, Artur Gramacki, Jarosław Gramacki (2013)

International Journal of Applied Mathematics and Computer Science

The Probability Density Function (PDF) is a key concept in statistics. Constructing the most adequate PDF from the observed data is still an important and interesting scientific problem, especially for large datasets. PDFs are often estimated using nonparametric data-driven methods. One of the most popular nonparametric method is the Kernel Density Estimator (KDE). However, a very serious drawback of using KDEs is the large number of calculations required to compute them, especially to find the...

Growth rates and average optimality in risk-sensitive Markov decision chains

Karel Sladký (2008)

Kybernetika

In this note we focus attention on characterizations of policies maximizing growth rate of expected utility, along with average of the associated certainty equivalent, in risk-sensitive Markov decision chains with finite state and action spaces. In contrast to the existing literature the problem is handled by methods of stochastic dynamic programming on condition that the transition probabilities are replaced by general nonnegative matrices. Using the block-triangular decomposition of a collection...

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