Search results for "vector"

On a class of languages with holonomic generating functions

2017

We define a class of languages (RCM) obtained by considering Regular languages, linear Constraints on the number of occurrences of symbols and Morphisms. The class RCM presents some interesting closure properties, and contains languages with holonomic generating functions. As a matter of fact, RCM is related to one-way 1-reversal bounded k-counter machines and also to Parikh automata on letters. Indeed, RCM is contained in L-NFCM but not in L-DFCM, and strictly includes L-CPA. We conjecture that L-DFCM subset of RCM

On singularities of discontinuous vector fields

2003

Abstract The subject of this paper concerns the classification of typical singularities of a class of discontinuous vector fields in 4D. The focus is on certain discontinuous systems having some symmetric properties.

Rigidity of quasisymmetric mappings on self-affine carpets

2016

We show that the class of quasisymmetric maps between horizontal self-affine carpets is rigid. Such maps can only exist when the dimensions of the carpets coincide, and in this case, the quasisymmetric maps are quasi-Lipschitz. We also show that horizontal self-affine carpets are minimal for the conformal Assouad dimension.

Multiplications of Distributions in One Dimension and a First Application to Quantum Field Theory

2002

In a previous paper we introduced a class of multiplications of distributions in one dimension. Here we furnish different generalizations of the original definition and we discuss some applications of these procedures to the multiplication of delta functions and to quantum field theory. © 2002 Elsevier Science (USA).

A new paradigm for pattern classification: Nearest Border Techniques

2013

Published version of a chapter in the book: AI 2013: Advances in Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-03680-9_44 There are many paradigms for pattern classification. As opposed to these, this paper introduces a paradigm that has not been reported in the literature earlier, which we shall refer to as the Nearest Border (NB) paradigm. The philosophy for developing such a NB strategy is as follows: Given the training data set for each class, we shall first attempt to create borders for each individual class. After that, we advocate that testing is accomplished by assigning the test sample to the class whose border it lies closest to…

High Expression of Human CYP2C in Immortalized Human Liver Epithelial Cells

2010

Cell lines stably expressing high levels of single isozymes of human CYP2C genes (CYP2C8, CYP2C9, CYP2C18 and CYP2C19) have been successfully generated by transfecting liver epithelial human cells (THLE) with an appropriate expression vector. To this aim, cDNAs encoding for each CYP2C gene were inserted by blunt-ended cloning into the unique insertion site of the singular expression vector pCMVneo. The recombinant pCMV2C8, pCMV2C9, pCMV2C18 and pCMV2C19 vectors were liposome-mediated transfected into THLE cells. The resulting transgenic cells, designated as T5-2C8, T5-2C9, T5-2C18 and T5-2C19, were cloned and the expression of the ectopic gene, mRNA and protein, was investigated by RT-PCR a…

Differential properties of the Moreau envelope

2014

International audience; In a vector space endowed with a uniformly Gâteaux differentiable norm, it is proved that the Moreau envelope enjoys many remarkable differential properties and that its subdifferential can be completely described through a certain approximate proximal mapping. This description shows in particular that the Moreau envelope is essentially directionally smooth. New differential properties are derived for the distance function associated with a closed set. Moreover, the analysis, when applied to the investigation of the convexity of Tchebyshev sets, allows us to recover several known results in the literature and to provide some new ones.

The on-line curvilinear component analysis (onCCA) for real-time data reduction

2015

Real time pattern recognition applications often deal with high dimensional data, which require a data reduction step which is only performed offline. However, this loses the possibility of adaption to a changing environment. This is also true for other applications different from pattern recognition, like data visualization for input inspection. Only linear projections, like the principal component analysis, can work in real time by using iterative algorithms while all known nonlinear techniques cannot be implemented in such a way and actually always work on the whole database at each epoch. Among these nonlinear tools, the Curvilinear Component Analysis (CCA), which is a non-convex techni…

Corrigendum to “Imaginary time propagation code for large-scale two-dimensional eigenvalue problems in magnetic fields” [Comput. Phys. Comm. 184(3) (…

2016

Channel selection in Cognitive Radio Networks: A Switchable Bayesian Learning Automata approach

2013

We consider the problem of a user operating within a Cognitive Radio Network (CRN) which involves N channels each associated with a Primary User (PU). The problem consists of allocating a channel which, at any given time instant is not being used by a PU, to a Secondary User (SU). Within our study, we assume that a SU is allowed to perform “channel switching”, i.e., to choose an alternate channel S times (where S +1 ≤ N) if the previous choice does not lead to a channel which is vacant. The paper first presents a formal probabilistic model for the problem itself, referred to as the Formal Secondary Channel Selection (FSCS) problem, and the characteristics of the FSCS are then analyzed. Ther…