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Discrete Techniques Of Parameter Estimation
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Book Synopsis Parameter Estimation and Inverse Problems by : Richard C. Aster
Download or read book Parameter Estimation and Inverse Problems written by Richard C. Aster and published by Elsevier. This book was released on 2018-10-16 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who do not have an extensive mathematical background. The book is complemented by a companion website that includes MATLAB codes that correspond to examples that are illustrated with simple, easy to follow problems that illuminate the details of particular numerical methods. Updates to the new edition include more discussions of Laplacian smoothing, an expansion of basis function exercises, the addition of stochastic descent, an improved presentation of Fourier methods and exercises, and more. - Features examples that are illustrated with simple, easy to follow problems that illuminate the details of a particular numerical method - Includes an online instructor's guide that helps professors teach and customize exercises and select homework problems - Covers updated information on adjoint methods that are presented in an accessible manner
Book Synopsis Inverse Problem Theory and Methods for Model Parameter Estimation by : Albert Tarantola
Download or read book Inverse Problem Theory and Methods for Model Parameter Estimation written by Albert Tarantola and published by SIAM. This book was released on 2005-01-01 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: While the prediction of observations is a forward problem, the use of actual observations to infer the properties of a model is an inverse problem. Inverse problems are difficult because they may not have a unique solution. The description of uncertainties plays a central role in the theory, which is based on probability theory. This book proposes a general approach that is valid for linear as well as for nonlinear problems. The philosophy is essentially probabilistic and allows the reader to understand the basic difficulties appearing in the resolution of inverse problems. The book attempts to explain how a method of acquisition of information can be applied to actual real-world problems, and many of the arguments are heuristic.
Book Synopsis Discrete Techniques of Parameter Estimation by : J. M. C. Mendel
Download or read book Discrete Techniques of Parameter Estimation written by J. M. C. Mendel and published by . This book was released on 1973 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Discrete Techniques of Parameter Estimation by : Jerry M. Mendel
Download or read book Discrete Techniques of Parameter Estimation written by Jerry M. Mendel and published by . This book was released on 1973 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Equation error formulation of parameter estimation problems; Least-squares parameter estimation; Minimum-variance parameter estimation; Stochastic-gradient parameter estimation; Estimation of time-varying parameters.
Book Synopsis Discrete Choice Methods with Simulation by : Kenneth Train
Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Book Synopsis Identification and System Parameter Estimation 1982 by : G. A. Bekey
Download or read book Identification and System Parameter Estimation 1982 written by G. A. Bekey and published by Elsevier. This book was released on 2016-06-06 with total page 869 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identification and System Parameter Estimation 1982 covers the proceedings of the Sixth International Federation of Automatic Control (IFAC) Symposium. The book also serves as a tribute to Dr. Naum S. Rajbman. The text covers issues concerning identification and estimation, such as increasing interrelationships between identification/estimation and other aspects of system theory, including control theory, signal processing, experimental design, numerical mathematics, pattern recognition, and information theory. The book also provides coverage regarding the application and problems faced by several engineering and scientific fields that use identification and estimation, such as biological systems, traffic control, geophysics, aeronautics, robotics, economics, and power systems. Researchers from all scientific fields will find this book a great reference material, since it presents topics that concern various disciplines.
Book Synopsis Modelling and Parameter Estimation of Dynamic Systems by : J.R. Raol
Download or read book Modelling and Parameter Estimation of Dynamic Systems written by J.R. Raol and published by IET. This book was released on 2004-08-13 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed examination of the estimation techniques and modeling problems. The theory is furnished with several illustrations and computer programs to promote better understanding of system modeling and parameter estimation.
Book Synopsis Parameter Estimation Techniques and Applications in Aircraft Flight Testing by :
Download or read book Parameter Estimation Techniques and Applications in Aircraft Flight Testing written by and published by . This book was released on 1974 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model by : A. Terry Morris
Download or read book Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model written by A. Terry Morris and published by . This book was released on 1999 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Lessons in Estimation Theory for Signal Processing, Communications, and Control by : Jerry M. Mendel
Download or read book Lessons in Estimation Theory for Signal Processing, Communications, and Control written by Jerry M. Mendel and published by Pearson Education. This book was released on 1995-03-14 with total page 891 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation theory is a product of need and technology. As a result, it is an integral part of many branches of science and engineering. To help readers differentiate among the rich collection of estimation methods and algorithms, this book describes in detail many of the important estimation methods and shows how they are interrelated. Written as a collection of lessons, this book introduces readers o the general field of estimation theory and includes abundant supplementary material.
Book Synopsis Parameter Estimation in Engineering and Science by : James Vere Beck
Download or read book Parameter Estimation in Engineering and Science written by James Vere Beck and published by James Beck. This book was released on 1977 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to and survey of parameter estimation; Probability; Introduction to statistics; Parameter estimation methods; Introduction to linear estimation; Matrix analysis for linear parameter estimation; Minimization of sum of squares functions for models nonlinear in parameters; Design of optimal experiments.
Book Synopsis Control, Identification, and Input Optimization by : Robert Kalaba
Download or read book Control, Identification, and Input Optimization written by Robert Kalaba and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a self-contained text devoted to the numerical determination of optimal inputs for system identification. It presents the current state of optimal inputs with extensive background material on optimization and system identification. The field of optimal inputs has been an area of considerable research recently with important advances by R. Mehra, G. c. Goodwin, M. Aoki, and N. E. Nahi, to name just a few eminent in vestigators. The authors' interest in optimal inputs first developed when F. E. Yates, an eminent physiologist, expressed the need for optimal or preferred inputs to estimate physiological parameters. The text assumes no previous knowledge of optimal control theory, numerical methods for solving two-point boundary-value problems, or system identification. As such it should be of interest to students as well as researchers in control engineering, computer science, biomedical en gineering, operations research, and economics. In addition the sections on beam theory should be of special interest to mechanical and civil en gineers and the sections on eigenvalues should be of interest to numerical analysts. The authors have tried to present a balanced viewpoint; however, primary emphasis is on those methods in which they have had first-hand experience. Their work has been influenced by many authors. Special acknowledgment should go to those listed above as well as R. Bellman, A. Miele, G. A. Bekey, and A. P. Sage. The book can be used for a two-semester course in control theory, system identification, and optimal inputs.
Book Synopsis New Developments in Parsing Technology by : H. Bunt
Download or read book New Developments in Parsing Technology written by H. Bunt and published by Springer Science & Business Media. This book was released on 2004-06-29 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parsing can be defined as the decomposition of complex structures into their constituent parts, and parsing technology as the methods, the tools, and the software to parse automatically. Parsing is a central area of research in the automatic processing of human language. Parsers are being used in many application areas, for example question answering, extraction of information from text, speech recognition and understanding, and machine translation. New developments in parsing technology are thus widely applicable. This book contains contributions from many of today's leading researchers in the area of natural language parsing technology. The contributors describe their most recent work and a diverse range of techniques and results. This collection provides an excellent picture of the current state of affairs in this area. This volume is the third in a series of such collections, and its breadth of coverage should make it suitable both as an overview of the current state of the field for graduate students, and as a reference for established researchers.
Book Synopsis Classical and Modern Numerical Analysis by : Azmy S. Ackleh
Download or read book Classical and Modern Numerical Analysis written by Azmy S. Ackleh and published by CRC Press. This book was released on 2009-07-20 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classical and Modern Numerical Analysis: Theory, Methods and Practice provides a sound foundation in numerical analysis for more specialized topics, such as finite element theory, advanced numerical linear algebra, and optimization. It prepares graduate students for taking doctoral examinations in numerical analysis.The text covers the main areas o
Book Synopsis Handbook of Digital Signal Processing by : Douglas F. Elliott
Download or read book Handbook of Digital Signal Processing written by Douglas F. Elliott and published by Elsevier. This book was released on 2013-10-22 with total page 1022 pages. Available in PDF, EPUB and Kindle. Book excerpt: FROM THE PREFACE: Many new useful ideas are presented in this handbook, including new finite impulse response (FIR) filter design techniques, half-band and multiplierless FIR filters, interpolated FIR (IFIR) structures, and error spectrum shaping.
Book Synopsis Lectures on Adaptive Parameter Estimation by : C. Richard Johnson
Download or read book Lectures on Adaptive Parameter Estimation written by C. Richard Johnson and published by Prentice Hall. This book was released on 1988 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parameter Estimation in Stochastic Differential Equations by : Jaya P. N. Bishwal
Download or read book Parameter Estimation in Stochastic Differential Equations written by Jaya P. N. Bishwal and published by Springer. This book was released on 2007-09-26 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
