Search results for "Linear Algebra."
showing 10 items of 552 documents
Efficient Pruning LMI Conditions for Branch-and-Prune Rank and Chirality-Constrained Estimation of the Dual Absolute Quadric
2014
International audience; We present a new globally optimal algorithm for self- calibrating a moving camera with constant parameters. Our method aims at estimating the Dual Absolute Quadric (DAQ) under the rank-3 and, optionally, camera centers chirality constraints. We employ the Branch-and-Prune paradigm and explore the space of only 5 parameters. Pruning in our method relies on solving Linear Matrix Inequality (LMI) feasibility and Generalized Eigenvalue (GEV) problems that solely depend upon the entries of the DAQ. These LMI and GEV problems are used to rule out branches in the search tree in which a quadric not satisfy- ing the rank and chirality conditions on camera centers is guarantee…
The Power of the “Pursuit” Learning Paradigm in the Partitioning of Data
2019
Traditional Learning Automata (LA) work with the understanding that the actions are chosen purely based on the “state” in which the machine is. This modus operandus completely ignores any estimation of the Random Environment’s (RE’s) (specified as \(\mathbb {E}\)) reward/penalty probabilities. To take these into consideration, Estimator/Pursuit LA utilize “cheap” estimates of the Environment’s reward probabilities to make them converge by an order of magnitude faster. This concept is quite simply the following: Inexpensive estimates of the reward probabilities can be used to rank the actions. Thereafter, when the action probability vector has to be updated, it is done not on the basis of th…
Designing Paper Machine Headbox Using GA
2003
Abstract A non-smooth biobjective optimization problem for designing the shape of a slice channel in a paper machine headbox is described. The conflicting goals defining the optimization problem are the ones determining important quality properties of produced paper: 1) basis weight should be even and 2) the wood fibers of paper should mainly be oriented to the machine direction across the width of the whole paper machine. The novelty of the considered approach is that maximum deviations are used instead of least squares when objective functions are formed. For the solution of this problem, a multiobjective genetic algorithm based on nondominated sorting is considered. The numerical results…
Mass transportation on sub-Riemannian structures of rank two in dimension four
2017
International audience; This paper is concerned with the study of the Monge optimal transport problem in sub-Riemannian manifolds where the cost is given by the square of the sub-Riemannian distance. Our aim is to extend previous results on existence and uniqueness of optimal transport maps to cases of sub-Riemannian structures which admit many singular minimizing geodesics. We treat here the case of sub-Riemannian structures of rank two in dimension four.
Equivalence Relations on Stonian Spaces
1996
Abstract Quotient spaces of locally compact Stonian spaces which generalize in some sense the concept of Stone representation space of a Boolean algebra are investigated emphasizing the measure theoretical point of view, and a representation theorem for finitely additive measures is proved.
Bases and quasi-reflexivity in Fréchet spaces
2005
A Frechet space E is quasi-reflexive if, either dim(E″/E) < ∞, or E″[β(E″,E′)]/E is isomorphic to ω. A Frechet space E is totally quasi-reflexive if every separated quotient is quasi-reflexive. In this paper we show, using Schauder bases, that E is totally quasi-reflexive if and only if it is isomorphic to a closed subspace of a countable product of quasi-reflexive Banach spaces. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Selected Topics on Banach Space Theory
2019
Basic topics on Banach space theory needed for the text are reviewed. Hahn-Banach theorem, Baire’s theorem, uniform boundedness principle, closed graph theorem, weak topologies, Banach-Alaoglu theorem, unconditional basis, Banach sequence spaces, summing operators, factorable operators, cotype, Kahane inequality.
Determination of Particle Size Distributions in Multiphase Systems Containing Nonspherical Fluid Particles
2015
The presented results are obtained by means of an automated image analysis software capable of measuring particle diameters in photographs taken in situ by a 2D photo-optical measurement device. Initially, the applicability of this measurement method must be proven for fluid particle systems on the basis of spherical-shaped particles. As a first approach in targeting the issue of irregularly shaped fluid particles, a pure gas-liquid system is analyzed to investigate the influence of the variation of operating parameters. In the second step, the spherical shape is changed by reducing the surface-active auxiliaries. The usage of shape factors helps to interpret the appearance of the 2D projec…
A 3D mesoscopic approach for discrete dislocation dynamics
2001
In recent years a noticeable renewed interest in modeling dislocations at the mesoscopic scale has been developed leading to significant advances in the field. This interest has arisen from a desire to link the atomistic and macroscopic length scales. In this context, we have recently developed a 3D-discrete dislocation dynamics model (DDD) based on a nodal discretization of the dislocations. We present here the basis of our DDD model and two examples of studies with single and multiple slip planes.
Neural Network Techniques for Metal Forming Design
1993
Neural networks are computing structures able to predict the behaviour of a system on the basis of the knowledge of facts; main characteristic of a network is the capability to find a rule in a very complex environment. In the paper a neural network, based on the results of FEM simulations, is utilized to predict the occurrence of defects in a forward extrusion metal forming process. In particular a three layers neural network, relating the operative parameters with the failure or the success of the working process, has been used and the back-propagation algorithm has been employed to train the network. Few experimental data were enough to train the neural network allowing to achieve better…