Grassmann manifold of aJH-algebra

We study the set of rankp idempotents in a topologically simple Hilbert Jordan algebra (JH-algebra for short). To produce the differential geometric structure on, we establish Jordan algebraic results concerning the structure of some two-generator subalgebras. We identify geodesics, the Riemannian distance and the sectional curvature of by using the Jordan algebraic structure.     

Tensor products over abelian Walgebras

Tensor products of Calgebras over an abelian Walgebra are studied. The minimal Cnorm on is shown to be just the quotient of the minimal Cnorm on if or is exact.

     

An energy-transport model for semiconductors derived from the Boltzmann equation

An energy-transport model is rigorously derived from the Boltzmann transport equation of semiconductors under the hypothesis that the energy gain or loss of the electrons by the phonon collisions is weak. Retaining at leading order electron-electron collisions and elastic collisions (i.e., impurity scattering and the elastic part of phonon collisions), a rigorous diffusion limit of the Boltzmann equation can be carried over, which leads to a set of diffusion equations for the electron density and temperature. The derivation is given in both the degenerate and nondegenerate cases.     

On pasting -weights

Theorem 3 gives a condition when two -weights can be ``pasted' together to yield another -weight. It is subsequently used in Example 6 to give an example that shows that a necessary condition by Gohberg, Krupnik, and Spitkovsky is not sufficient.

     

Bias in modal parameters due to aliasing in the time domain

This paper deals with some aliasing effects in the time domain that can lead to unacceptable misestimations of modal parameters. When a frequency response function of a vibrating system is sampled and inverse Fourier transformed, the resulting impulse response is given by an infinite geometric series, the single term of which is the impulse response itself shifted in time. For this reason, some modal parameters, if estimated in the time domain, are biased; in particular, while the damping factor and the natural frequency are not influenced by the aliasing phenomenon, the magnitude and phase of the residue can be highly biased. Corrective terms are theoretically evaluated and their efficiency is shown in numerical simulations.

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Sommario In questo articolo e' presentato un metodo per correggere gli errori che si compiono nella stima di alcuni parametri modali, quando essi vengono ricavati nel dominio del tempo. Infatti se la funzione di risposta in frequenza e' ottenuta con eccitazioni particolari—quali ad esempio lo pseudo-random, lo stepped-sine a passo costante o lo sweep in frequenza-la risposta impulsiva, ottenuta per mezzo dell'antitrasformata discreta di Fourier, risulta periodica, con periodo pari all'inverso della spaziatura tra le righe spettrali. Cio' comporta un errore nella stima dell'ampiezza e della fase del residuo, mentre nessuna conseguenza si ha sulla frequenza naturale e sul fattore di smorzamento. L'errore sulle stime risulta tanto piu' grande, quanto meno smorzata e' la risposta impulsiva all'interno dell'intervallo di osservazione.Partendo dall'inviluppo e dalla fase istantanea dei segnali complessi, ottenibili per mezzo della trasformata di Hilbert, si sono ricavati i termini correttivi sia per il modulo, che per la fase del residuo. La validita' delle correzioni e' mostrata con esempi numerici.

     

Riemann—Hilbert Problem for the First Order Elliptic Systems

In this article we discuss the Riemann—Hilbert problems for the first order elliptic systems and prove the existence of the solution by means of general analytic function theory and Cauchy integral formula.     

Strong Convergence Theorems for the Generalized Viscosity Implicit Rules of Asymptotically Nonexpansive Mappings in the Intermediate Sense in Hilbert Spaces

Abstract

The aim of this paper is to introduce the generalized viscosity implicit rules of one asymptotically nonexpansive mapping in the intermediate sense in Hilbert spaces. We obtain some strong convergence theorems under certain assumptions imposed on the parameters. We also give a numerical example to support our main results. The results obtained in this paper improve and extend many recent ones in this culture.     

Sobolev H1 geometry of the symplectomorphism group

For a closed symplectic manifold $(M,\omega )$ with compatible Riemannian metric g we study the Sobolev $H^1$ geometry of the group of all $H^s$ diffeomorphisms on M which preserve the symplectic structure. We show that, for sufficiently large s, the $H^1$ metric admits globally defined geodesics and the corresponding exponential map is a non-linear Fredholm map of index zero. Finally, we show that the $H^1$ metric carries conjugate points via some simple examples.     

Automorphisms of Hilbert schemes of points on a generic projective K3 surface

We study automorphisms of the Hilbert scheme of n points on a generic projective K3 surface S, for any . We show that is either trivial or generated by a non‐symplectic involution and we determine numerical and divisorial conditions which allow us to distinguish between the two cases. As an application of these results we prove that, for any , there exist infinitely many admissible degrees for the polarization of the K3 surface S such that admits a non‐natural involution. This provides a generalization of the results of [7] for .     

Continuum versus discrete networks,graph Laplacians,and reproducing kernel Hilbert spaces

Motivated by applications to machine learning, we construct a reversible and irreducible Markov chain whose state space is a certain collection of measurable sets of a chosen l.c.h. space $\mathfrak{X}$. We study the resulting network (connected undirected graph), including transience, Royden and Riesz decompositions, and kernel factorization. We describe a construction for Hilbert spaces of signed measures which comes equipped with a new notion of reproducing kernels and there is a unique solution to a regularized optimization problem involving the approximation of $L^2$ functions by functions of finite energy. The latter has applications to machine learning (for Markov random fields, for example).