Cantitate/Preț
Produs

Linear Stochastic Systems: A Geometric Approach to Modeling, Estimation and Identification: Series in Contemporary Mathematics, cartea 1

Autor Anders Lindquist, Giorgio Picci
en Limba Engleză Paperback – 29 oct 2016
This book presents a treatise on the theory and modeling of second-order stationary processes, including an exposition on selected application areas that are important in the engineering and applied sciences. The foundational issues regarding stationary processes dealt with in the beginning of the book have a long history, starting in the 1940s with the work of Kolmogorov, Wiener, Cramér and his students, in particular Wold, and have since been refined and complemented by many others. Problems concerning the filtering and modeling of stationary random signals and systems have also been addressed and studied, fostered by the advent of modern digital computers, since the fundamental work of R.E. Kalman in the early 1960s. The book offers a unified and logically consistent view of the subject based on simple ideas from Hilbert space geometry and coordinate-free thinking. In this framework, the concepts of stochastic state space and state space modeling, based on the notionof the conditional independence of past and future flows of the relevant signals, are revealed to be fundamentally unifying ideas. The book, based on over 30 years of original research, represents a valuable contribution that will inform the fields of stochastic modeling, estimation, system identification, and time series analysis for decades to come. It also provides the mathematical tools needed to grasp and analyze the structures of algorithms in stochastic systems theory.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 100193 lei  6-8 săpt.
  Springer Berlin, Heidelberg – 29 oct 2016 100193 lei  6-8 săpt.
Hardback (1) 100840 lei  6-8 săpt.
  Springer Berlin, Heidelberg – 11 mai 2015 100840 lei  6-8 săpt.

Din seria Series in Contemporary Mathematics

Preț: 100193 lei

Preț vechi: 122186 lei
-18% Nou

Puncte Express: 1503

Preț estimativ în valută:
19181 19938$ 15903£

Carte tipărită la comandă

Livrare economică 05-19 februarie 25

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783662526187
ISBN-10: 3662526182
Pagini: 796
Ilustrații: XV, 781 p. 37 illus.
Dimensiuni: 155 x 235 x 40 mm
Greutate: 1.1 kg
Ediția:Softcover reprint of the original 1st ed. 2015
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Series in Contemporary Mathematics

Locul publicării:Berlin, Heidelberg, Germany

Cuprins

Introduction.- Geometry of Second-Order Random Processes.- Spectral Representation of Stationary Processes.- Innovations, Wold Decomposition, and Spectral Factorization.- Wold Decomposition and Spectral Factorization in Continuous Time.- Linear Finite-Dimensional Stochastic Systems.- The Geometry of Splitting Subspaces.- Markovian Representations.- Proper Markovian Representations in Hardy Space.- Stochastic Realization Theory in Continuous Time.- Stochastic Balancing and Model Reduction.- Finite-Interval Stochastic Realization and Partial Realization Theory.- Subspace Identification for Time Series.- Zero Dynamics and the Geometry of the Riccati Inequality.- Smoothing and Interpolation.- Acausal Linear Stochastic Models and Spectral Factorization.- Stochastic Systems with Inputs.- Appendix A. Basic Principles of Deterministic Realization Theory.- Appendix B. Some Topics in Linear Algebra and Hilbert Space Theory

Recenzii

“The purpose of this book is to present the mathematical background necessary for understanding the linear state-space modeling of second-order random processes and its applications to estimation and identification theory. … this monograph is an excellent reference for researchers interested in geometric theory of stochastic realization and its applications.” (Viorica M. Ungureanu, Mathematical Reviews, January, 2016)

Textul de pe ultima copertă

This book presents a treatise on the theory and modeling of second-order stationary processes, including an exposition on selected application areas that are important in the engineering and applied sciences. The foundational issues regarding stationary processes dealt with in the beginning of the book have a long history, starting in the 1940s with the work of Kolmogorov, Wiener, Cramér and his students, in particular Wold, and have since been refined and complemented by many others. Problems concerning the filtering and modeling of stationary random signals and systems have also been addressed and studied, fostered by the advent of modern digital computers, since the fundamental work of R.E. Kalman in the early 1960s. The book offers a unified and logically consistent view of the subject based on simple ideas from Hilbert space geometry and coordinate-free thinking. In this framework, the concepts of stochastic state space and state space modeling, based on the notion of the conditional independence of past and future flows of the relevant signals, are revealed to be fundamentally unifying ideas. The book, based on over 30 years of original research, represents a valuable contribution that will inform the fields of stochastic modeling, estimation, system identification, and time series analysis for decades to come. It also provides the mathematical tools needed to grasp and analyze the structures of algorithms in stochastic systems theory.

Caracteristici

Maximizes reader insights into stochastic modeling, estimation, system identification, and time series analysis Reveals the concepts of stochastic state space and state space modeling to unify the idea Supports further exploration through a unified and logically consistent view of the subject