Search results for "Affine"
showing 10 items of 183 documents
External derivations of internal groupoids
2008
If His a G-crossed module, the set of derivations of Gin H is a monoid under the Whitehead product of derivations. We interpret the Whitehead product using the correspondence between crossed modules and internal groupoids in the category of groups. Working in the general context of internal groupoids in a finitely complete category, we relate derivations to holomorphisms, translations, affine transformations, and to the embedding category of a groupoid. (C) 2007 Elsevier B.V. All rights reserved.
Fast equivariant JADE
2013
Independent component analysis (ICA) is a widely used signal processing tool having applications in various fields of science. In this paper we focus on affine equivariant ICA methods. Two such well-established estimation methods, FOBI and JADE, diagonalize certain fourth order cumulant matrices to extract the independent components. FOBI uses one cumulant matrix only, and is therefore computationally very fast. However, it is not able to separate identically distributed components which is a major drawback. JADE overcomes this restriction. Unfortunately, JADE uses a huge number of cumulant matrices and is computationally very heavy in high-dimensional cases. In this paper, we hybridize the…
Rationally integrable vector fields and rational additive group actions
2016
International audience; We characterize rational actions of the additive group on algebraic varieties defined over a field of characteristic zero in terms of a suitable integrability property of their associated velocity vector fields. This extends the classical correspondence between regular actions of the additive group on affine algebraic varieties and the so-called locally nilpotent derivations of their coordinate rings. Our results lead in particular to a complete characterization of regular additive group actions on semi-affine varieties in terms of their associated vector fields. Among other applications, we review properties of the rational counterpart of the Makar-Limanov invariant…
An affine scaling method using a class of differential barrier functions: primal approach
2020
International audience; In this paper we propose a family of affine scaling interior point algorithms, called galpv4, using a primal approach, based on a large class of differential barrier functions. We show that these algorithms are in fact an extension and generalization of the classical affine scaling algorithm based on the well-known log barrier function. After carrying out a complete convergence analysis, we select some of these algorithms for comparison with the classical affine scaling algorithm, performed with the help of the familiar Netlib test set.
NEAR-RINGS AND GROUPS OF AFFINE MAPPINGS
2013
We classify semi-topological locally compact and semi-algebraic near-rings R where the set of non-invertible elements of R forms an ideal I of R such that the multiplicative group of R/I acts sharply transitively on I\{0}. To achieve our results we use as a main tool the classi cation of locally compact and algebraic (2; 2)-transformation groups given in two previuos papers.
Structure of equilibrium states on self-affine sets and strict monotonicity of affinity dimension
2017
A fundamental problem in the dimension theory of self-affine sets is the construction of high- dimensional measures which yield sharp lower bounds for the Hausdorff dimension of the set. A natural strategy for the construction of such high-dimensional measures is to investigate measures of maximal Lyapunov dimension; these measures can be alternatively interpreted as equilibrium states of the singular value function introduced by Falconer. Whilst the existence of these equilibrium states has been well-known for some years their structure has remained elusive, particularly in dimensions higher than two. In this article we give a complete description of the equilibrium states of the singular …
Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction
2014
Abstract This paper deals with the problem of adaptive output feedback neural network controller design for a SISO non-affine nonlinear system. Since in practice all system states are not available in output measurement, an observer is designed to estimate these states. In comparison with the existing approaches, the current method does not require any information about the sign of control gain. In order to handle the unknown sign of the control direction, the Nussbaum-type function is utilized. In order to approximate the unknown nonlinear function, neural network is firstly exploited, and then to compensate the approximation error and external disturbance a robustifying term is employed. …
Project duration evaluated using affine arithmetic
2016
A civil engineering work can be performed by organizing the available resources (manpower, equipment and materials) in many different ways. Each different configuration results in a realization time and a cost that a building company has to bear. To produce reliable duration forecasts and money savings, it is essential to take into account all the uncertainties involved in the project operations. Generally, since it is impractical to process numerous uncertain variables - also undefined from a statistical point of view -, traditional probabilistic methods involve application difficulties for complex environments such as construction sites. To properly handle this issue, the authors propose …
The squared symmetric FastICA estimator
2017
In this paper we study the theoretical properties of the deflation-based FastICA method, the original symmetric FastICA method, and a modified symmetric FastICA method, here called the squared symmetric FastICA. This modification is obtained by replacing the absolute values in the FastICA objective function by their squares. In the deflation-based case this replacement has no effect on the estimate since the maximization problem stays the same. However, in the symmetric case we obtain a different estimate which has been mentioned in the literature, but its theoretical properties have not been studied at all. In the paper we review the classic deflation-based and symmetric FastICA approaches…
Deflation-Based FastICA With Adaptive Choices of Nonlinearities
2014
Deflation-based FastICA is a popular method for independent component analysis. In the standard deflation-base d approach the row vectors of the unmixing matrix are extracted one after another always using the same nonlinearities. In prac- tice the user has to choose the nonlinearities and the efficiency and robustness of the estimation procedure then strongly depends on this choice as well as on the order in which the components are extracted. In this paper we propose a novel adaptive two- stage deflation-based FastICA algorithm that (i) allows one to use different nonlinearities for different components and (ii) optimizes the order in which the components are extracted. Based on a consist…