Measurement Data Modeling and Parameter Estimation

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Publisher : CRC Press
ISBN 13 : 1439853797
Total Pages : 540 pages
Book Rating : 4.95/5 ( download)

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Book Synopsis Measurement Data Modeling and Parameter Estimation by : Zhengming Wang

Download or read book Measurement Data Modeling and Parameter Estimation written by Zhengming Wang and published by CRC Press. This book was released on 2016-04-19 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the theories, methods, and application techniques of the measurement data mathematical modeling and parameter estimation. It seeks to build a bridge between mathematical theory and engineering practice in the measurement data processing field so theoretical researchers and technical engineers can communicate. It is organized with abundant materials, such as illustrations, tables, examples, and exercises. The authors create examples to apply mathematical theory innovatively to measurement and control engineering. Not only does this reference provide theoretical knowledge, it provides information on first hand experiences.

Modelling and Parameter Estimation of Dynamic Systems

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Publisher : IET
ISBN 13 : 0863413633
Total Pages : 405 pages
Book Rating : 4.36/5 ( download)

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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.

Data Modeling for Metrology and Testing in Measurement Science

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Publisher : Springer Science & Business Media
ISBN 13 : 0817648046
Total Pages : 499 pages
Book Rating : 4.46/5 ( download)

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Book Synopsis Data Modeling for Metrology and Testing in Measurement Science by : Franco Pavese

Download or read book Data Modeling for Metrology and Testing in Measurement Science written by Franco Pavese and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods and focusing on techniques with a broad range of real-world applications. The book will be useful as a textbook for graduate students, or as a training manual in the fields of calibration and testing. The work may also serve as a reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement science.

Modelling and Parameter Estimation of Dynamic Systems

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Publisher : IET
ISBN 13 : 9780863413636
Total Pages : 408 pages
Book Rating : 4.33/5 ( download)

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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 408 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.

Classification, Parameter Estimation and State Estimation

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Publisher : John Wiley & Sons
ISBN 13 : 0470090146
Total Pages : 440 pages
Book Rating : 4.45/5 ( download)

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Book Synopsis Classification, Parameter Estimation and State Estimation by : Ferdinand van der Heijden

Download or read book Classification, Parameter Estimation and State Estimation written by Ferdinand van der Heijden and published by John Wiley & Sons. This book was released on 2005-06-10 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Model Calibration and Parameter Estimation

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Publisher : Springer
ISBN 13 : 1493923234
Total Pages : 621 pages
Book Rating : 4.36/5 ( download)

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Book Synopsis Model Calibration and Parameter Estimation by : Ne-Zheng Sun

Download or read book Model Calibration and Parameter Estimation written by Ne-Zheng Sun and published by Springer. This book was released on 2015-07-01 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Propagation Channel Characterization, Parameter Estimation, and Modeling for Wireless Communications

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Publisher : John Wiley & Sons
ISBN 13 : 1118188233
Total Pages : 408 pages
Book Rating : 4.31/5 ( download)

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Book Synopsis Propagation Channel Characterization, Parameter Estimation, and Modeling for Wireless Communications by : Xuefeng Yin

Download or read book Propagation Channel Characterization, Parameter Estimation, and Modeling for Wireless Communications written by Xuefeng Yin and published by John Wiley & Sons. This book was released on 2016-10-24 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive reference giving a thorough explanation of propagation mechanisms, channel characteristics results, measurement approaches and the modelling of channels Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are then presented, which include conventional spectral-based estimation, the specular-path-model based high-resolution method, and the newly derived power spectrum estimation methods. Measurement results are used to compare the performance of the different estimation methods. The third part gives a complete introduction to different modelling approaches. Among them, both scattering theoretical channel modelling and measurement-based channel modelling approaches are detailed. This part also approaches how to utilize these two modelling approaches to investigate wireless channels for conventional cellular systems and some new emerging communication systems. This three-part approach means the book caters for the requirements of the audiences at different levels, including readers needing introductory knowledge, engineers who are looking for more advanced understanding, and expert researchers in wireless system design as a reference. Presents technical explanations, illustrated with examples of the theory in practice Discusses results applied to 4G communication systems and other emerging communication systems, such as relay, CoMP, and vehicle-to-vehicle rapid time-variant channels Can be used as comprehensive tutorial for students or a complete reference for engineers in industry Includes selected illustrations in color Program downloads available for readers Companion website with program downloads for readers and presentation slides and solution manual for instructors Essential reading for Graduate students and researchers interested in the characteristics of propagation channel, or who work in areas related to physical layer architectures, air interfaces, navigation, and wireless sensing

Bayesian Inference

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Publisher : Springer Science & Business Media
ISBN 13 : 366206006X
Total Pages : 275 pages
Book Rating : 4.63/5 ( download)

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Book Synopsis Bayesian Inference by : Hanns L. Harney

Download or read book Bayesian Inference written by Hanns L. Harney and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving a longstanding problem in the physical sciences, this text and reference generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. The text is written at introductory level, with many examples and exercises.

Modeling and Parameter Estimation for Heterogeneous Cell Populations

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Publisher : Logos Verlag Berlin GmbH
ISBN 13 : 3832533982
Total Pages : 143 pages
Book Rating : 4.84/5 ( download)

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Book Synopsis Modeling and Parameter Estimation for Heterogeneous Cell Populations by : Jan Hasenauer

Download or read book Modeling and Parameter Estimation for Heterogeneous Cell Populations written by Jan Hasenauer and published by Logos Verlag Berlin GmbH. This book was released on 2013 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most of the modeling performed in biology aims at achieving a quantitative description and understanding of the intracellular signaling pathways within a "typical cell". However, in many biologically important situations even genetically identical cell populations show a heterogeneous response. This means that individual members of the cell population behave differently. Such situations require the study of cell-to-cell variability and the development of models for heterogeneous cell populations. The main contribution of this thesis is the development of unifying modeling frameworks for signal transduction and proliferation processes in heterogeneous cell populations. These modeling frameworks allow for the detailed description of individual cells as well as differences between them. In contrast to many existing modeling approaches, the proposed frameworks allow for a direct comparison of model predictions with available data. Beyond this, the proposed population models can be simulated efficiently and, by exploiting the model structures, we are able to develop model-tailored Bayesian parameter estimation methods. These methods enable the calculation of the optimal parameter estimates, as well as the evaluation of the parameter and prediction uncertainties. The proposed tools allow for novel insights in population dynamics, in particular the model-based characterization of population heterogeneity and cellular subgroups. This is illustrated for two different application examples: pro- and anti-apoptotic signaling, which is interesting in the context of cancer therapy, and immune cell proliferation.

Identification of Continuous-Time Systems

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Publisher : CRC Press
ISBN 13 : 1000732908
Total Pages : 94 pages
Book Rating : 4.00/5 ( download)

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Book Synopsis Identification of Continuous-Time Systems by : Allamaraju Subrahmanyam

Download or read book Identification of Continuous-Time Systems written by Allamaraju Subrahmanyam and published by CRC Press. This book was released on 2019-12-06 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation—computational or realized through prefilters, to preserve the system parameters in their native CT form—and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research. This modest volume is intended to be a useful addition to the literature on identifying CT systems.