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Parameter Estimation in Engineering and Science

Parameter Estimation in Engineering and Science
Author: James Vere Beck
Publisher: James Beck
Total Pages: 540
Release: 1977
Genre: Mathematics
ISBN: 9780471061182

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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.


Parameter Estimation for Scientists and Engineers

Parameter Estimation for Scientists and Engineers
Author: Adriaan van den Bos
Publisher: Wiley-Interscience
Total Pages: 296
Release: 2007-07-16
Genre: Mathematics
ISBN:

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Parameter Estimation and Inverse Problems

Parameter Estimation and Inverse Problems
Author: Richard C. Aster
Publisher: Elsevier
Total Pages: 404
Release: 2018-10-16
Genre: Science
ISBN: 0128134232

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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


Entropy-Based Parameter Estimation in Hydrology

Entropy-Based Parameter Estimation in Hydrology
Author: V.P. Singh
Publisher: Springer Science & Business Media
Total Pages: 382
Release: 2013-04-17
Genre: Science
ISBN: 9401714312

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Since the pioneering work of Shannon in the late 1940's on the development of the theory of entropy and the landmark contributions of Jaynes a decade later leading to the development of the principle of maximum entropy (POME), the concept of entropy has been increasingly applied in a wide spectrum of areas, including chemistry, electronics and communications engineering, data acquisition and storage and retreival, data monitoring network design, ecology, economics, environmental engineering, earth sciences, fluid mechanics, genetics, geology, geomorphology, geophysics, geotechnical engineering, hydraulics, hydrology, image processing, management sciences, operations research, pattern recognition and identification, photogrammetry, psychology, physics and quantum mechanics, reliability analysis, reservoir engineering, statistical mechanics, thermodynamics, topology, transportation engineering, turbulence modeling, and so on. New areas finding application of entropy have since continued to unfold. The entropy concept is indeed versatile and its applicability widespread. In the area of hydrology and water resources, a range of applications of entropy have been reported during the past three decades or so. This book focuses on parameter estimation using entropy for a number of distributions frequently used in hydrology. In the entropy-based parameter estimation the distribution parameters are expressed in terms of the given information, called constraints. Thus, the method lends itself to a physical interpretation of the parameters. Because the information to be specified usually constitutes sufficient statistics for the distribution under consideration, the entropy method provides a quantitative way to express the information contained in the distribution.


Classification, Parameter Estimation and State Estimation

Classification, Parameter Estimation and State Estimation
Author: Ferdinand van der Heijden
Publisher: John Wiley & Sons
Total Pages: 440
Release: 2005-06-10
Genre: Science
ISBN: 0470090146

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Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MATLAB. 'Prtools' is a powerful MATLAB toolbox for pattern recognition and is written and owned by one of the co-authors, B. Duin of the Delft University of Technology. After an introductory chapter, the book provides the theoretical construction for classification, estimation and state estimation. The book also deals with the skills required to bring the theoretical concepts to practical systems, and how to evaluate these systems. Together with the many examples in the chapters, the book is accompanied by a MATLAB toolbox for pattern recognition and classification. The appendix provides the necessary documentation for this toolbox as well as an overview of the most useful functions from these toolboxes. With its integrated and unified approach to classification, parameter estimation and state estimation, this book is a suitable practical supplement in existing university courses in pattern classification, optimal estimation and data analysis. Covers all contemporary main methods for classification and estimation. Integrated approach to classification, parameter estimation and state estimation Highlights the practical deployment of theoretical issues. Provides a concise and practical approach supported by MATLAB toolbox. Offers exercises at the end of each chapter and numerous worked out examples. PRtools toolbox (MATLAB) and code of worked out examples available from the internet Many examples showing implementations in MATLAB Enables students to practice their skills using a MATLAB environment


Parameter Estimation for Scientists and Engineers

Parameter Estimation for Scientists and Engineers
Author: Adriaan van den Bos
Publisher: John Wiley & Sons
Total Pages: 296
Release: 2007-08-03
Genre: Technology & Engineering
ISBN: 9780470173855

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The subject of this book is estimating parameters of expectation models of statistical observations. The book describes the most important aspects of the subject for applied scientists and engineers. This group of users is often not aware of estimators other than least squares. Therefore one purpose of this book is to show that statistical parameter estimation has much more to offer than least squares estimation alone. In the approach of this book, knowledge of the distribution of the observations is involved in the choice of estimators. A further advantage of the chosen approach is that it unifies the underlying theory and reduces it to a relatively small collection of coherent, generally applicable principles and notions.


Model Calibration and Parameter Estimation

Model Calibration and Parameter Estimation
Author: Ne-Zheng Sun
Publisher: Springer
Total Pages: 638
Release: 2015-07-01
Genre: Mathematics
ISBN: 1493923234

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This three-part book provides a comprehensive and systematic introduction to these challenging topics such as model calibration, parameter estimation, reliability assessment, and data collection design. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and statistical frameworks, Part 2 is dedicated to system identification, hyperparameter estimation, and model dimension reduction, and Part 3 considers how to collect data and construct reliable models for prediction and decision-making. For the first time, topics such as multiscale inversion, stochastic field parameterization, level set method, machine learning, global sensitivity analysis, data assimilation, model uncertainty quantification, robust design, and goal-oriented modeling, are systematically described and summarized in a single book from the perspective of model inversion, and elucidated with numerical examples from environmental and water resources modeling. Readers of this book will not only learn basic concepts and methods for simple parameter estimation, but also get familiar with advanced methods for modeling complex systems. Algorithms for mathematical tools used in this book, such as numerical optimization, automatic differentiation, adaptive parameterization, hierarchical Bayesian, metamodeling, Markov chain Monte Carlo, are covered in details. This book can be used as a reference for graduate and upper level undergraduate students majoring in environmental engineering, hydrology, and geosciences. It also serves as an essential reference book for professionals such as petroleum engineers, mining engineers, chemists, mechanical engineers, biologists, biology and medical engineering, applied mathematicians, and others who perform mathematical modeling.


Scientific Computing in Chemical Engineering

Scientific Computing in Chemical Engineering
Author: Frerich Keil
Publisher: Springer Science & Business Media
Total Pages: 274
Release: 2012-12-06
Genre: Science
ISBN: 3642801498

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Scientific Computing in Chemical Engineering gives the state of the art from the point of view of the numerical mathematicians as well as from the engineers. The application of modern methods in numerical mathematics on problems in chemical engineering, especially reactor modeling, process simulation, process optimization and the use of parallel computing is detailed.


Parameter Estimation and Hypothesis Testing in Linear Models

Parameter Estimation and Hypothesis Testing in Linear Models
Author: Karl-Rudolf Koch
Publisher: Springer Science & Business Media
Total Pages: 344
Release: 2013-03-09
Genre: Mathematics
ISBN: 3662039761

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A treatment of estimating unknown parameters, testing hypotheses and estimating confidence intervals in linear models. Readers will find here presentations of the Gauss-Markoff model, the analysis of variance, the multivariate model, the model with unknown variance and covariance components and the regression model as well as the mixed model for estimating random parameters. A chapter on the robust estimation of parameters and several examples have been added to this second edition. The necessary theorems of vector and matrix algebra and the probability distributions of test statistics are derived so as to make this book self-contained. Geodesy students as well as those in the natural sciences and engineering will find the emphasis on the geodetic application of statistical models extremely useful.