Author: G. KiriakidisPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Optimal Test Signal Design
Author: G. KiriakidisOptimal Test Signal Design for Linear S.I.S.O. System Indentification
Author: G. C. GoodwinDynamic System Identification: Experiment Design and Data Analysis
Author: GoodwinPublisher: Academic Press
ISBN: 0080956459
Category : Computers
Languages : en
Pages : 303
Book Description
Dynamic System Identification: Experiment Design and Data Analysis
Optimal Input Signals for Parameter Estimation
Author: Ewaryst RafajłowiczPublisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110383349
Category : History
Languages : en
Pages : 232
Book Description
The aim of this book is to provide methods and algorithms for the optimization of input signals so as to estimate parameters in systems described by PDE’s as accurate as possible under given constraints. The optimality conditions have their background in the optimal experiment design theory for regression functions and in simple but useful results on the dependence of eigenvalues of partial differential operators on their parameters. Examples are provided that reveal sometimes intriguing geometry of spatiotemporal input signals and responses to them. An introduction to optimal experimental design for parameter estimation of regression functions is provided. The emphasis is on functions having a tensor product (Kronecker) structure that is compatible with eigenfunctions of many partial differential operators. New optimality conditions in the time domain and computational algorithms are derived for D-optimal input signals when parameters of ordinary differential equations are estimated. They are used as building blocks for constructing D-optimal spatio-temporal inputs for systems described by linear partial differential equations of the parabolic and hyperbolic types with constant parameters. Optimality conditions for spatially distributed signals are also obtained for equations of elliptic type in those cases where their eigenfunctions do not depend on unknown constant parameters. These conditions and the resulting algorithms are interesting in their own right and, moreover, they are second building blocks for optimality of spatio-temporal signals. A discussion of the generalizability and possible applications of the results obtained is presented.
Advanced Simulation in Biomedicine
Author: Dietmar P.F. MöllerPublisher: Springer Science & Business Media
ISBN: 1441986146
Category : Computers
Languages : en
Pages : 206
Book Description
This book presents a collection of invited contributions, each reflecting an area of biomedicine in which simulation techniques have been successfully applied. Thus, it provides a state-of-the-art survey of simulation techniques in a variety of biomedical applications. Chapter one presents the conceptual framework for advanced simulations such as parallel processing in biological systems. Chapter two focuses on structured biological modeling based on the bond graph method. This is followed by an up-to-date account of advanced simulation of a variety of sophisticated biomedical processes. The authors provide many insights into how computer simulation techniques and tools can be applied to research problems in biomedicine. The idea for this book arose out of the daily work by experts in their field and reflects developing areas. Therefore, I think the material is timely and hope that the work described will be an encouragement for others. It is the objective of this book to present advanced simulation techniques in biomedicine and outline current research, as well as to point out open problems, in this dynamic field. Finally, I wish to express my thanks to those colleagues who have made this book possible with their contributions.
Inverse Engineering Handbook
Author: Keith A. WoodburyPublisher: CRC Press
ISBN: 1420041614
Category : Mathematics
Languages : en
Pages : 481
Book Description
Inverse problems have been the focus of a growing number of research efforts over the last 40 years-and rightly so. The ability to determine a "cause" from an observed "effect" is a powerful one. Researchers now have at their disposal a variety of techniques for solving inverse problems, techniques that go well beyond those useful for relatively si
System Identification 2003
Author: Paul Van Den HofPublisher: Elsevier
ISBN: 0080913156
Category : Technology & Engineering
Languages : en
Pages : 2092
Book Description
The scope of the symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control, ranging from theoretical, methodological and scientific developments to a large variety of (engineering) application areas. It is the intention of the organizers to promote SYSID 2003 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas. Relevant topics for the symposium program include: Identification of linear and multivariable systems, identification of nonlinear systems, including neural networks, identification of hybrid and distributed systems, Identification for control, experimental modelling in process control, vibration and modal analysis, model validation, monitoring and fault detection, signal processing and communication, parameter estimation and inverse modelling, statistical analysis and uncertainty bounding, adaptive control and data-based controller tuning, learning, data mining and Bayesian approaches, sequential Monte Carlo methods, including particle filtering, applications in process control systems, motion control systems, robotics, aerospace systems, bioengineering and medical systems, physical measurement systems, automotive systems, econometrics, transportation and communication systems *Provides the latest research on System Identification*Contains contributions written by experts in the field*Part of the IFAC Proceedings Series which provides a comprehensive overview of the major topics in control engineering.
System Identification Advances and Case Studies
Author: Publisher: Academic Press
ISBN: 0080956351
Category : Mathematics
Languages : en
Pages : 606
Book Description
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; andmethods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory.As a result, the book represents a blend of new methods in general computational analysis,and specific, but also generic, techniques for study of systems theory ant its particularbranches, such as optimal filtering and information compression. - Best operator approximation,- Non-Lagrange interpolation,- Generic Karhunen-Loeve transform- Generalised low-rank matrix approximation- Optimal data compression- Optimal nonlinear filtering
Trends and Progress in System Identification
Author: Pieter EykhoffPublisher: Elsevier
ISBN: 1483148661
Category : Mathematics
Languages : en
Pages : 419
Book Description
Trends and Progress in System Identification is a three-part book that focuses on model considerations, identification methods, and experimental conditions involved in system identification. Organized into 10 chapters, this book begins with a discussion of model method in system identification, citing four examples differing on the nature of the models involved, the nature of the fields, and their goals. Subsequent chapters describe the most important aspects of model theory; the ""classical"" methods and time series estimation; application of least squares and related techniques for the estimation of dynamic system parameters; the maximum likelihood and error prediction methods; and the modern development of statistical methods. Non-parametric approaches, identification of nonlinear systems by piecewise approximation, and the minimax identification are then explained. Other chapters explore the Bayesian approach to system identification; choice of input signals; and choice and effect of different feedback configurations in system identification. This book will be useful for control engineers, system scientists, biologists, and members of other disciplines dealing withdynamical relations.
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