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Exact And Approximate Modeling Of Linear Systems
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Book Synopsis Exact and Approximate Modeling of Linear Systems by : Ivan Markovsky
Download or read book Exact and Approximate Modeling of Linear Systems written by Ivan Markovsky and published by SIAM. This book was released on 2006-01-01 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title elegantly introduces the behavioral approach to mathematical modeling, an approach that requires models to be viewed as sets of possible outcomes rather than to be a priori bound to particular representations. The authors discuss exact and approximate fitting of data by linear, bilinear, and quadratic static models and linear dynamic models, a formulation that enables readers to select the most suitable representation for a particular purpose. This book presents exact subspace-type and approximate optimization-based identification methods, as well as representation-free problem formulations, an overview of solution approaches, and software implementation. Readers will find an exposition of a wide variety of modeling problems starting from observed data. The presented theory leads to algorithms that are implemented in C language and in MATLAB.
Book Synopsis Identification of Linear Systems by : J. Schoukens
Download or read book Identification of Linear Systems written by J. Schoukens and published by Elsevier. This book was released on 2014-06-28 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on the problem of accurate modeling of linear systems. It presents a thorough description of a method of modeling a linear dynamic invariant system by its transfer function. The first two chapters provide a general introduction and review for those readers who are unfamiliar with identification theory so that they have a sufficient background knowledge for understanding the methods described later. The main body of the book looks at the basic method used by the authors to estimate the parameter of the transfer function, how it is possible to optimize the excitation signals. Further chapters extend the estimation method proposed. Applications are then discussed and the book concludes with practical guidelines which illustrate the method and offer some rules-of-thumb.
Book Synopsis Low-Rank Approximation by : Ivan Markovsky
Download or read book Low-Rank Approximation written by Ivan Markovsky and published by Springer. This book was released on 2018-08-03 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of applications from systems and control theory to psychometrics being described. Special knowledge of the application fields is not required. The second edition of /Low-Rank Approximation/ is a thoroughly edited and extensively rewritten revision. It contains new chapters and sections that introduce the topics of: • variable projection for structured low-rank approximation;• missing data estimation;• data-driven filtering and control;• stochastic model representation and identification;• identification of polynomial time-invariant systems; and• blind identification with deterministic input model. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB^® /Octave examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis. “Each chapter is completed with a new section of exercises to which complete solutions are provided.” Low-Rank Approximation (second edition) is a broad survey of the Low-Rank Approximation theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well.
Book Synopsis Control of Uncertain Systems: Modelling, Approximation, and Design by : Bruce A. Francis
Download or read book Control of Uncertain Systems: Modelling, Approximation, and Design written by Bruce A. Francis and published by Taylor & Francis. This book was released on 2006-03-07 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Festschrift contains a collection of articles by friends, co-authors, colleagues, and former Ph.D. students of Keith Glover, Professor of Engineering at the University of Cambridge, on the occasion of his sixtieth birthday. Professor Glover's scientific work spans a wide variety of topics, the main themes being system identification, model reduction and approximation, robust controller synthesis, and control of aircraft and engines. The articles in this volume are a tribute to Professor Glover's seminal work in these areas.
Book Synopsis Latent Variable Analysis and Signal Separation by : Emmanuel Vincent
Download or read book Latent Variable Analysis and Signal Separation written by Emmanuel Vincent and published by Springer. This book was released on 2015-08-14 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented – 29 accepted as oral presentations and 32 accepted as poster presentations – were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear blind source separation; sparse and low rank modeling for acoustic signal processing.
Book Synopsis Exact Modelling and Identifiability of Linear Systems by : Christiaan Heij
Download or read book Exact Modelling and Identifiability of Linear Systems written by Christiaan Heij and published by . This book was released on 1988 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Iterative Methods for Sparse Linear Systems by : Yousef Saad
Download or read book Iterative Methods for Sparse Linear Systems written by Yousef Saad and published by SIAM. This book was released on 2003-04-01 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics of Computing -- General.
Book Synopsis Introduction to Applied Linear Algebra by : Stephen Boyd
Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
Book Synopsis Model Emergent Dynamics in Complex Systems by : A. J. Roberts
Download or read book Model Emergent Dynamics in Complex Systems written by A. J. Roberts and published by SIAM. This book was released on 2014-12-18 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: Arising out of the growing interest in and applications of modern dynamical systems theory, this book explores how to derive relatively simple dynamical equations that model complex physical interactions. The author’s objectives are to use sound theory to explore algebraic techniques, develop interesting applications, and discover general modeling principles. Model Emergent Dynamics in Complex Systems unifies into one powerful and coherent approach the many varied extant methods for mathematical model reduction and approximation. Using mathematical models at various levels of resolution and complexity, the book establishes the relationships between such multiscale models and clarifying difficulties and apparent paradoxes and addresses model reduction for systems, resolves initial conditions, and illuminates control and uncertainty. The basis for the author’s methodology is the theory and the geometric picture of both coordinate transforms and invariant manifolds in dynamical systems; in particular, center and slow manifolds are heavily used. The wonderful aspect of this approach is the range of geometric interpretations of the modeling process that it produces—simple geometric pictures inspire sound methods of analysis and construction. Further, pictures drawn of state spaces also provide a route to better assess a model’s limitations and strengths. Geometry and algebra form a powerful partnership and coordinate transforms and manifolds provide a powerfully enhanced and unified view of a swathe of other complex system modeling methodologies such as averaging, homogenization, multiple scales, singular perturbations, two timing, and WKB theory. Audience Advanced undergraduate and graduate students, engineers, scientists, and other researchers who need to understand systems and modeling at different levels of resolution and complexity will all find this book useful.
Book Synopsis Intelligent Systems and Applications by : Yaxin Bi
Download or read book Intelligent Systems and Applications written by Yaxin Bi and published by Springer Nature. This book was released on 2019-08-23 with total page 1312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a remarkable collection of chapters covering a wide range of topics in the areas of intelligent systems and artificial intelligence, and their real-world applications. It gathers the proceedings of the Intelligent Systems Conference 2019, which attracted a total of 546 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process, after which 190 were selected for inclusion in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made it possible to tackle a host of problems more effectively. This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for an international conference as a venue for reporting on the latest innovations and trends. This book collects both theory and application based chapters on virtually all aspects of artificial intelligence; presenting state-of-the-art intelligent methods and techniques for solving real-world problems, along with a vision for future research, it represents a unique and valuable asset.
Book Synopsis Low-Rank Approximation by : Ivan Markovsky
Download or read book Low-Rank Approximation written by Ivan Markovsky and published by Springer. This book was released on 2019-01-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of applications from systems and control theory to psychometrics being described. Special knowledge of the application fields is not required. The second edition of /Low-Rank Approximation/ is a thoroughly edited and extensively rewritten revision. It contains new chapters and sections that introduce the topics of: • variable projection for structured low-rank approximation;• missing data estimation;• data-driven filtering and control;• stochastic model representation and identification;• identification of polynomial time-invariant systems; and• blind identification with deterministic input model. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB^® /Octave examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis. “Each chapter is completed with a new section of exercises to which complete solutions are provided.” Low-Rank Approximation (second edition) is a broad survey of the Low-Rank Approximation theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well.
Book Synopsis Mathematics of Epidemics on Networks by : István Z. Kiss
Download or read book Mathematics of Epidemics on Networks written by István Z. Kiss and published by Springer. This book was released on 2017-06-08 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by: Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book; Presenting different mathematical approaches to formulate exact and solvable models; Identifying the concrete links between approximate models and their rigorous mathematical representation; Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity; Providing a reference source for advanced undergraduate students, as well as doctoral students, postdoctoral researchers and academic experts who are engaged in modeling stochastic processes on networks; Providing software that can solve differential equation models or directly simulate epidemics on networks. Replete with numerous diagrams, examples, instructive exercises, and online access to simulation algorithms and readily usable code, this book will appeal to a wide spectrum of readers from different backgrounds and academic levels. Appropriate for students with or without a strong background in mathematics, this textbook can form the basis of an advanced undergraduate or graduate course in both mathematics and other departments alike.
Download or read book Dynamical Systems written by Simon Diner and published by World Scientific. This book was released on 1986 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book commemorates the centenary of the birth of Georges David Birhoff, the father of the theory of Dynamical Systems. It consists of a volume of dedicated papers, reflecting the intellectual revolution of his work. This book is divided into four parts: Fundamental Paradigms ? Chaos, Turbulence, Attractors, Bifurcations; Dynamical Systems and Microphysics; Self-Organization and Biological Dynamical Systems; Epistemology and History.
Book Synopsis Dynamical Systems - A Renewal Of Mechanism: Contennial Of Georges David Birkhoff by : Simon Diner
Download or read book Dynamical Systems - A Renewal Of Mechanism: Contennial Of Georges David Birkhoff written by Simon Diner and published by World Scientific. This book was released on 1986-09-01 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book commemorates the centenary of the birth of Georges David Birhoff, the father of the theory of Dynamical Systems. It consists of a volume of dedicated papers, reflecting the intellectual revolution of his work. This book is divided into four parts: Fundamental Paradigms — Chaos, Turbulence, Attractors, Bifurcations; Dynamical Systems and Microphysics; Self-Organization and Biological Dynamical Systems; Epistemology and History.
Download or read book ESAIM. written by and published by . This book was released on 2008 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Linear and Nonlinear System Modeling by : Tamal Roy
Download or read book Linear and Nonlinear System Modeling written by Tamal Roy and published by John Wiley & Sons. This book was released on 2024-09-06 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written and edited by a team of experts in the field, this exciting new volume presents the cutting-edge techniques, latest trends, and state-of-the-art practical applications in linear and nonlinear system modeling. Mathematical modeling of control systems is, essentially, extracting the essence of practical problems into systematic mathematical language. In system modeling, mathematical expression deals with modeling and its applications. It is characterized that how a modeling competency can be categorized and its activity can contribute to building up these competencies. Mathematical modeling of a practical system is an attractive field of research and an advanced subject with a variety of applications. The main objective of mathematical modeling is to predict the behavior of the system under different operating conditions and to design and implement efficient control strategies to achieve the desired performance. A considerable effort has been directed to the development of models, which must be understandable and easy to analyze. It is a very difficult task to develop mathematical modeling of complicated practical systems considering all its possible high-level non-linearity and cross couple dynamics. Although mathematical modeling of nonlinear systems sounds quite interesting, it is difficult to formulate the general solution to analyze and synthesize nonlinear dynamical systems. Most of the natural processes are nonlinear, having very high computational complexity of several numerical issues. It is impossible to create any general solution or individual procedure to develop exact modeling of a non-linear system, which is often improper and too complex for engineering practices. Therefore, some series of approximation procedures are used, in order to get some necessary knowledge about the nonlinear system dynamics. There are several complicated mathematical approaches for solving these types of problems, such as functional analysis, differential geometry or the theory of nonlinear differential equations.
Book Synopsis How to Solve Large Linear Systems by : Aleksa Srdanov
Download or read book How to Solve Large Linear Systems written by Aleksa Srdanov and published by Universal-Publishers. This book was released on 2019-12-01 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving the linear equation system n x n can also be a problem for a computer, even when the number of equations and unknowns is relatively small (a few hundred). All existing methods are burdened by at least one of the following problems: 1) Complexity of computation expressed through the number of operations required to be done to obtaining solution; 2) Unrestricted growth of the size of the intermediate result, which causes overflow and underflow problems; 3) Changing the value of some coefficients in the input system, which causes the instability of the solution; 4) Require certain conditions for convergence, etc. In this paper an approximate and exact methods for solving a system of linear equations with an arbitrary number of equations and the same number of unknowns is presented. All the mentioned problems can be avoided by the proposed methods. It is possible to define an algorithm that does not solve the system of equations in the usual mathematical way, but still finds its exact solution in the exact number of steps already defined. The methods consist of simple computations that are not cumulative. At the same time, the number of operations is acceptable even for a relatively large number of equations and unknowns. In addition, the algorithms allows the process to start from an arbitrary initial n-tuple and always leads to the exact solution if it exists.
