Author: Israel GohbergPublisher: American Mathematical Soc.
ISBN: 9780821886502
Category : Mathematics
Languages : en
Pages : 402
Book Description
Introduction to the Theory of Linear Nonselfadjoint Operators
Author: Israel GohbergPublisher: American Mathematical Soc.
ISBN: 9780821886502
Category : Mathematics
Languages : en
Pages : 402
Book Description
Introduction to the Theory of Linear Nonselfadjoint Operators
Author: Yiśrāʿēl Z. GohbergIntroduction to the Theory of Linear Nonselfadjoint Operators in Hilbert Space
Author: I. C. GohbergPublisher:
ISBN: 9781470444365
Category : Hilbert space
Languages : en
Pages : 399
Book Description
Introduction to the Theory of Linear Nonselfadjoint Operators
Author: Israel GohbergPublisher:
ISBN:
Category : Hilbert space
Languages : en
Pages : 378
Book Description
Introductory to the Theory of Linear Nonselfadjoint Operators
Author: Izrail Tsudikovich GokhbergPublisher:
ISBN:
Category :
Languages : en
Pages : 378
Book Description
Introduction to the Theory of Linear Nonselfadjoint Operators, By I.C. Gohberg (And) M.G. Krein. (Translated From the Russian by A. Feinstein).
Author: Izrailʹ T︠S︡udikovich GokhbergPublisher:
ISBN:
Category : Linear operators
Languages : en
Pages : 378
Book Description
Introudction to the Theory of Linear Nonselfadjoint Operators
Author: I. C. GochbergIntroduction to the Theorie of Linear Nonselfadjoint Operators
Author: Israel GohbergTheory of Commuting Nonselfadjoint Operators
Author: M.S. LivsicPublisher: Springer Science & Business Media
ISBN: 940158561X
Category : Mathematics
Languages : en
Pages : 329
Book Description
Considering integral transformations of Volterra type, F. Riesz and B. Sz.-Nagy no ticed in 1952 that [49]: "The existence of such a variety of linear transformations, having the same spectrum concentrated at a single point, brings out the difficulties of characterization of linear transformations of general type by means of their spectra." Subsequently, spectral analysis has been developed for different classes of non selfadjoint operators [6,7,14,20,21,36,44,46,54]. It was then realized that this analysis forms a natural basis for the theory of systems interacting with the environment. The success of this theory in the single operator case inspired attempts to create a general theory in the much more complicated case of several commuting operators with finite-dimensional imaginary parts. During the past 10-15 years such a theory has been developed, yielding fruitful connections with algebraic geometry and sys tem theory. Our purpose in this book is to formulate the basic problems appearing in this theory and to present its main results. It is worth noting that, in addition to the joint spectrum, the corresponding algebraic variety and its global topological characteristics play an important role in the classification of commuting operators. For the case of a pair of operators these are: 1. The corresponding algebraic curve, and especially its genus. 2. Certain classes of divisors - or certain line bundles - on this curve.
Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
Author: Tailen HsingPublisher: John Wiley & Sons
ISBN: 0470016914
Category : Mathematics
Languages : en
Pages : 363
Book Description
Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA). The self–contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self–adjoint and non self–adjoint operators. The probabilistic foundation for FDA is described from the perspective of random elements in Hilbert spaces as well as from the viewpoint of continuous time stochastic processes. Nonparametric estimation approaches including kernel and regularized smoothing are also introduced. These tools are then used to investigate the properties of estimators for the mean element, covariance operators, principal components, regression function and canonical correlations. A general treatment of canonical correlations in Hilbert spaces naturally leads to FDA formulations of factor analysis, regression, MANOVA and discriminant analysis. This book will provide a valuable reference for statisticians and other researchers interested in developing or understanding the mathematical aspects of FDA. It is also suitable for a graduate level special topics course.