00000cmm a22000004a 4500 UP-99796217611212080 Buklod 20241010135546.0 m go j cr cn |||aaaaa 241010s2011 gw ||||go||j| ||||||eng d 9783642219818 (eBook) 3642219802 (eBook) (iLib)UPD-00214608237 CSt DMLR rda eng DMLUC QA 276.8 Y68 2011eb Young, Peter C. author Recursive estimation and time-series analysis an introduction for the student and practitioner by Peter C. Young. 2nd edition. Berlin, Heidelberg Springer 2011 1 online resource (xviii, 504 pages) illustrations text rdacontent computer rdamedia online resource rdacarrier Communications and control engineering series Includes bibliographical references and index Introduction -- Part I Recursive Estimation of Parameters in Linear Regression Models -- Recursive Estimation: A Simple Tutorial Introduction -- Recursive Least Squares Estimation -- Recursive Estimation of Time Variable Parameters in Regression Models -- Unobserved Component Models -- Part II Recursive Estimation of Parameters in Transfer Function Models -- Transfer Function Models and the Limitations of Recursive Least Squares -- Optimal Identification and Estimation of Discrete-Time Transfer Function Models -- Optimal Identification and Estimation of Continuous-Time Transfer Function Models -- Identification of TF models in Closed-Loop -- Real-Time Recursive Parameter Estimation -- Part III Other Topics -- State-Dependent Parameter Estimation -- Data-Based Mechanistic (DBM) modeling -- Epilogue -- A. The K.F. Gauss derivation of recursive least squares -- B. Basic mathematical and statistical background -- C. Stochastic approximation -- D. Deterministic regularization and stochastic fixed interval smoothing -- E. The instantaneous cost function associated with the recursive least squares algorithm -- F. Maximum likelihood derivation of the refined instrumental variable algorithm -- G. The CAPTAIN toolbox for Matlab: an overview. IP-based subscription, access limited to within on-campus computer network. Access via Electronic Resources of the UPD University Library Website. 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 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 MatlabTM 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. Electronic reproduction. New York SpringerLink 2011. Available via World Wide Web through SpringerLink. Estimation theory. Time-series analysis. SpringerLink (Online service). http://link.springer.com/book/10.1007/978-3-642-21981-8 Available for University of the Philippines Diliman via SpringerLink. Click here to access FO UPD DMLR Electronic Resource