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This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed at Lancaster, for use in the Matlab TM software environment (see Appendix G). Consequently, the present version of the book is able to exploit the many computational routines that are contained in this widely available Toolbox, as well as some of the other routines in Matlab TM and its other toolboxes.The book is an introductory one on the topic of recursive estimation and it demonstrates how this approach to estimation, in its various forms, can be an impressive aid to the modelling of stochastic, dynamic systems. It is intended for undergraduate or Masters students who wish to obtain a grounding in this subject, or for practitioners in industry who may have heard of topics dealt with in this book and, while they want to know more about them, may have been deterred by the rather esoteric nature of some books in this challenging area of study.

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This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate all the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed by my colleagues and I at Lancaster, for use in the MatlabTM software environment (see Appendix G). Consequently, the present version of the book is able to exploit the many computational routines that are contained in this widely available Toolbox, as well as some of the other routines in Matlab and its other toolboxes.The book is an introductory one on the topic of recursive estimation and it demonstrates how this approach to estimation, in its various forms, can be an impressive aid to the modelling of stochastic, dynamic systems. It is intended for undergraduate or Masters students who wish to obtain a grounding in this subject, or for practitioners in industry who may have heard of topics dealt with in this book and, while they want to know more about them, may have been deterred by the rather esoteric nature of some books in this challenging area of study.

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Erscheinungsdatum: 28.11.2014, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Recursive Estimation and Time-Series Analysis, Titelzusatz: An Introduction for the Student and Practitioner, Auflage: 2. Auflage von 2014 // 2nd ed. 2011, Autor: Young, Peter C., Verlag: Springer Berlin Heidelberg // Springer Berlin, Sprache: Englisch, Schlagworte: Wahrscheinlichkeitsrechnung und Statistik // Maschinenbau: Festkörpermechanik // Regelungstechnik // Nachrichtententechnik // Telekommunikation, Rubrik: Elektronik // Elektrotechnik, Nachrichtentechnik, Seiten: 524, Informationen: Paperback, Gewicht: 785 gr, Verkäufer: averdo

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Erscheinungsdatum: 10/2011, Medium: Buch, Einband: Gebunden, Titel: Recursive Estimation and Time-Series Analysis, Titelzusatz: An Introduction for the Student and Practitioner, Auflage: 2. Auflage von 2011 // 2nd Edition, Autor: Young, Peter C., Verlag: Springer-Verlag GmbH // Springer Berlin, Sprache: Englisch, Schlagworte: Roboter // Robotik // Industrieroboter // Mathematik // Statistik // Stochastik // Wahrscheinlichkeitsrechnung // Körper // physikalisch // Festkörper // Mechanik // Nachrichtentechnik // Kommunikation // Technik // Telekommunikation // Ingenieurwissenschaft // Ingenieurwissenschaftler // Maschinenbau // Wahrscheinlichkeitsrechnung und Statistik // Naturwissenschaften // allgemein // Maschinenbau: Festkörpermechanik // Nachrichtententechnik // Mathematische Physik // Ingenieurswesen // Maschinenbau allgemein, Rubrik: Elektronik // Elektrotechnik, Nachrichtentechnik, Seiten: 502, Abbildungen: 122 schwarz-weiße und 4 farbige Abbildungen, Herkunft: NIEDERLANDE (NL), Informationen: Book, Gewicht: 936 gr, Verkäufer: averdo

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Parallelizing compilers is one of the most important topics in parallel programming. It is developed to automatically parallelize sequential programs to reduce the burden of programming on parallel computers. At start it concentrates on parallelizing loops then it opens its scope to other aspects such as recursive functions. Consequently, new parallelizing compilers are proposed to automatically parallelize recursive functions in order to be executed efficiently on different parallel systems such as distributed memory massively parallel multicomputers and multiprocessors. A special concern has been for applications of divide-and-conquer algorithms. New algorithms for dependence analysis, partitioning, scheduling, and generating SPMD message passing program are introduced. Also new virtual topologies are proposed. Different types of recursive functions have been examined using variety of parallel machines. Ultimate performance measurements are used aiming at reaching optimality.

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In proof theory, ordinal analysis assigns ordinals (often large countable ordinals) to mathematical theories as a measure of their strength. The field was formed when Gerhard Gentzen in 1934 used cut elimination to prove, in modern terms, that the proof theoretic ordinal of Peano arithmetic is 0.Ordinal analysis concerns true, effective (recursive) theories that can interpret a sufficient portion of arithmetic to make statements about ordinal notations. The proof theoretic ordinal of such a theory is the smallest recursive ordinal that the theory cannot prove is well founded the supremum of all ordinals for which there exists a notation o in Kleene''s sense such that T proves that o is an ordinal notation. Equivalently, it is the supremum of all ordinals such that there exists a recursive relation R on (the set of natural numbers) which well-orders it with ordinal and such that T proves transfinite induction of arithmetical statements for R.

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Constructive Nonlinear Control presents a broad repertoire of constructive nonlinear designs not available in other works by widening the class of systems and design tools. Several streams of nonlinear control theory are merged and directed towards a constructive solution of the feedback stabilization problem. Analysis, geometric and asymptotic concepts are assembled as design tools for a wide variety of nonlinear phenomena and structures. Geometry serves as a guide for the construction of design procedures whilst analysis provides the robustness which geometry lacks. New recursive designs remove earlier restrictions on feedback passivation. Recursive Lyapunov designs for feedback, feedforward and interlaced structures result in feedback systems with optimality properties and stability margins. The design-oriented approach will make this work a valuable tool for all those who have an interest in control theory.

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