System Identification

Theory for the User
Author: Lennart Ljung
Publisher: Pearson Education
ISBN: 0132440539
Category: Technology & Engineering
Page: N.A
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The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples designed for Ljung's market-leading software, System Identification Toolbox for MATLAB. Ljung combines careful mathematics, a practical understanding of real-world applications, and extensive exercises. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods. Parameter estimation methods in a general prediction error setting. Frequency domain data and frequency domain interpretations. Asymptotic analysis of parameter estimates. Linear regressions, iterative search methods, and other ways to compute estimates. Recursive (adaptive) estimation techniques. Ljung also presents detailed coverage of the key issues that can make or break system identification projects, such as defining objectives, designing experiments, controlling the bias distribution of transfer-function estimates, and carefully validating the resulting models. The first edition of System Identification has been the field's most widely cited reference for over a decade. This new edition will be the new text of choice for anyone concerned with system identification theory and practice.

System Identification

An Introduction
Author: Karel J. Keesman
Publisher: Springer Science & Business Media
ISBN: 9780857295224
Category: Technology & Engineering
Page: 323
View: 2027
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System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering: • data-based identification – non-parametric methods for use when prior system knowledge is very limited; • time-invariant identification for systems with constant parameters; • time-varying systems identification, primarily with recursive estimation techniques; and • model validation methods. A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text. The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input–output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors’ Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable for self-tuition by practitioners looking to brush up on modern techniques. Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.

Mastering System Identification in 100 Exercises


Author: Johan Schoukens,Rik Pintelon,Yves Rolain
Publisher: John Wiley & Sons
ISBN: 1118218507
Category: Technology & Engineering
Page: 282
View: 3401
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This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring complex theoretical knowledge. The contents encompass state-of-the-art system identification methods, with both time and frequency domain system identification methods covered, including the pros and cons of each. Each chapter features MATLAB exercises, discussions of the exercises, accompanying MATLAB downloads, and larger projects that serve as potential assignments in this learn-by-doing resource.

System Identification

A Frequency Domain Approach
Author: Rik Pintelon,Johan Schoukens
Publisher: John Wiley & Sons
ISBN: 0470640375
Category: Science
Page: 743
View: 6612
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System identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and the designing of any electrical systems, they are vital in the fields of electrical, mechanical, civil, and chemical engineering. Focusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach. It high??lights many of the important steps in the identification process, points out the possible pitfalls to the reader, and illustrates the powerful tools that are available. Readers of this Second Editon will benefit from: MATLAB software support for identifying multivariable systems that is freely available at the website http://booksupport.wiley.com State-of-the-art system identification methods for both time and frequency domain data New chapters on non-parametric and parametric transfer function modeling using (non-)period excitations Numerous examples and figures that facilitate the learning process A simple writing style that allows the reader to learn more about the theo??retical aspects of the proofs and algorithms Unlike other books in this field, System Identification, Second Edition is ideal for practicing engineers, scientists, researchers, and both master's and PhD students in electrical, mechanical, civil, and chemical engineering.

Modeling of Dynamic Systems


Author: Lennart Ljung,Torkel Glad
Publisher: Prentice Hall
ISBN: 9780135970973
Category: Science
Page: 361
View: 9527
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Written by a recognized authority in the field of identification and control, this book draws together into a single volume the important aspects of system identification AND physical modelling. KEY TOPICS: Explores techniques used to construct mathematical models of systems based on knowledge from physics, chemistry, biology, etc. (e.g., techniques with so called bond-graphs, as well those which use computer algebra for the modeling work). Explains system identification techniques used to infer knowledge about the behavior of dynamic systems based on observations of the various input and output signals that are available for measurement. Shows how both types of techniques need to be applied in any given practical modeling situation. Considers applications, primarily simulation. For practicing engineers who are faced with problems of modeling.

Applied System Identification


Author: Jer-Nan Juang
Publisher: N.A
ISBN: 9780130792112
Category: Technology & Engineering
Page: 394
View: 7835
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Effective system identification includes the underlying methodologies, computational procedures, and their implementation. To this end, this volume presents readers with the mathematical background required to participate in the growing field of system identification as applied to engineering systems. Author Jer-Nan Juang provides a common basis for understanding the techniques developed under various disciplines. In addition, he attempts to bring the discipline of system identification up to date. Specifically Applied System Identification: provides an overview of the disciplines of modal testing used in structural engineering and system identification; presents time- and frequency-domain models used in the disciplines of structures and controls; identifies basic concepts and properties of the frequency response function; features a unified mathematical framework based on the theory of system realization to correlate some of the existing time-domain methods commonly used in modal testing; introduces readers to a new way of interpreting the input/output relationship via an observer for identification of a system model and its corresponding observer to characterize system uncertainties; proposes a simple, yet effective way of curve-fitting the frequency response data and of constructing a system model via matrix-fraction description methods; considers the identification problem of a system operating in closed-loop with an existing feedback controller; develops a unified mathematical framework to derive recursive algorithms for the fast transversal filter and the least-squares lattice filter. Whether used as a textbook or as an addition to your personal reference library, Applied System Identification offers an ideal opportunity to build a bridge between the disciplines of system identification as applied to controls and to modal testing.

Principles of System Identification

Theory and Practice
Author: Arun K. Tangirala
Publisher: CRC Press
ISBN: 143989602X
Category: Technology & Engineering
Page: 908
View: 7230
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Master Techniques and Successfully Build Models Using a Single Resource Vital to all data-driven or measurement-based process operations, system identification is an interface that is based on observational science, and centers on developing mathematical models from observed data. Principles of System Identification: Theory and Practice is an introductory-level book that presents the basic foundations and underlying methods relevant to system identification. The overall scope of the book focuses on system identification with an emphasis on practice, and concentrates most specifically on discrete-time linear system identification. Useful for Both Theory and Practice The book presents the foundational pillars of identification, namely, the theory of discrete-time LTI systems, the basics of signal processing, the theory of random processes, and estimation theory. It explains the core theoretical concepts of building (linear) dynamic models from experimental data, as well as the experimental and practical aspects of identification. The author offers glimpses of modern developments in this area, and provides numerical and simulation-based examples, case studies, end-of-chapter problems, and other ample references to code for illustration and training. Comprising 26 chapters, and ideal for coursework and self-study, this extensive text: Provides the essential concepts of identification Lays down the foundations of mathematical descriptions of systems, random processes, and estimation in the context of identification Discusses the theory pertaining to non-parametric and parametric models for deterministic-plus-stochastic LTI systems in detail Demonstrates the concepts and methods of identification on different case-studies Presents a gradual development of state-space identification and grey-box modeling Offers an overview of advanced topics of identification namely the linear time-varying (LTV), non-linear, and closed-loop identification Discusses a multivariable approach to identification using the iterative principal component analysis Embeds MATLAB® codes for illustrated examples in the text at the respective points Principles of System Identification: Theory and Practice presents a formal base in LTI deterministic and stochastic systems modeling and estimation theory; it is a one-stop reference for introductory to moderately advanced courses on system identification, as well as introductory courses on stochastic signal processing or time-series analysis.

System Identification


Author: T. S. Soderstrom,Petre G. Stoica
Publisher: N.A
ISBN: N.A
Category: Technology & Engineering
Page: 612
View: 4519
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Identification of Continuous-time Models from Sampled Data


Author: Hugues Garnier,Liuping Wang
Publisher: Springer Science & Business Media
ISBN: 9781848001619
Category: Technology & Engineering
Page: 413
View: 2526
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This is the first book dedicated to direct continuous-time model identification for 15 years. It cuts down on time spent hunting through journals by providing an overview of much recent research in an increasingly busy field. The CONTSID toolbox discussed in the final chapter gives an overview of developments and practical examples in which MATLAB® can be used for direct time-domain identification of continuous-time systems. This is a valuable reference for a broad audience.

Evolving Intelligent Systems

Methodology and Applications
Author: Plamen Angelov,Dimitar P. Filev,Nik Kasabov
Publisher: John Wiley & Sons
ISBN: 9780470569955
Category: Computers
Page: 416
View: 8481
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From theory to techniques, the first all-in-one resource for EIS There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications. Explains the following fundamental approaches for developing evolving intelligent systems (EIS): the Hierarchical Prioritized Structure the Participatory Learning Paradigm the Evolving Takagi-Sugeno fuzzy systems (eTS+) the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm Emphasizes the importance and increased interest in online processing of data streams Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems Introduces an integrated approach to incremental (real-time) feature extraction and classification Proposes a study on the stability of evolving neuro-fuzzy recurrent networks Details methodologies for evolving clustering and classification Reveals different applications of EIS to address real problems in areas of: evolving inferential sensors in chemical and petrochemical industry learning and recognition in robotics Features downloadable software resources Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.

Signal Analysis and Prediction


Author: Ales Prochazka,N.G. Kingsbury,P.J.W. Payner,J. Uhlir
Publisher: Springer Science & Business Media
ISBN: 1461217687
Category: Technology & Engineering
Page: 502
View: 3189
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Methods of signal analysis represent a broad research topic with applications in many disciplines, including engineering, technology, biomedicine, seismography, eco nometrics, and many others based upon the processing of observed variables. Even though these applications are widely different, the mathematical background be hind them is similar and includes the use of the discrete Fourier transform and z-transform for signal analysis, and both linear and non-linear methods for signal identification, modelling, prediction, segmentation, and classification. These meth ods are in many cases closely related to optimization problems, statistical methods, and artificial neural networks. This book incorporates a collection of research papers based upon selected contri butions presented at the First European Conference on Signal Analysis and Predic tion (ECSAP-97) in Prague, Czech Republic, held June 24-27, 1997 at the Strahov Monastery. Even though the Conference was intended as a European Conference, at first initiated by the European Association for Signal Processing (EURASIP), it was very gratifying that it also drew significant support from other important scientific societies, including the lEE, Signal Processing Society of IEEE, and the Acoustical Society of America. The organizing committee was pleased that the re sponse from the academic community to participate at this Conference was very large; 128 summaries written by 242 authors from 36 countries were received. In addition, the Conference qualified under the Continuing Professional Development Scheme to provide PD units for participants and contributors.

Block-oriented Nonlinear System Identification


Author: Fouad Giri,Er-Wei Bai
Publisher: Springer Science & Business Media
ISBN: 1849965129
Category: Technology & Engineering
Page: 426
View: 1083
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Block-oriented Nonlinear System Identification deals with an area of research that has been very active since the turn of the millennium. The book makes a pedagogical and cohesive presentation of the methods developed in that time. These include: iterative and over-parameterization techniques; stochastic and frequency approaches; support-vector-machine, subspace, and separable-least-squares methods; blind identification method; bounded-error method; and decoupling inputs approach. The identification methods are presented by authors who have either invented them or contributed significantly to their development. All the important issues e.g., input design, persistent excitation, and consistency analysis, are discussed. The practical relevance of block-oriented models is illustrated through biomedical/physiological system modelling. The book will be of major interest to all those who are concerned with nonlinear system identification whatever their activity areas. This is particularly the case for educators in electrical, mechanical, chemical and biomedical engineering and for practising engineers in process, aeronautic, aerospace, robotics and vehicles control. Block-oriented Nonlinear System Identification serves as a reference for active researchers, new comers, industrial and education practitioners and graduate students alike.

Adaptive Control

Second Edition
Author: Karl J. Åström,Björn Wittenmark
Publisher: Courier Corporation
ISBN: 0486319148
Category: Technology & Engineering
Page: 592
View: 426
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Suitable for advanced undergraduates and graduate students, this overview introduces theoretical and practical aspects of adaptive control, with emphasis on deterministic and stochastic viewpoints. 1995 edition.

System Identification, Environmental Modelling, and Control System Design


Author: Liuping Wang,Hugues Garnier
Publisher: Springer Science & Business Media
ISBN: 9780857299741
Category: Technology & Engineering
Page: 648
View: 9012
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This book is dedicated to Prof. Peter Young on his 70th birthday. Professor Young has been a pioneer in systems and control, and over the past 45 years he has influenced many developments in this field. This volume comprises a collection of contributions by leading experts in system identification, time-series analysis, environmetric modelling and control system design – modern research in topics that reflect important areas of interest in Professor Young’s research career. Recent theoretical developments in and relevant applications of these areas are explored treating the various subjects broadly and in depth. The authoritative and up-to-date research presented here will be of interest to academic researcher in control and disciplines related to environmental research, particularly those to with water systems. The tutorial style in which many of the contributions are composed also makes the book suitable as a source of study material for graduate students in those areas.

JOHNS HOPKINS NURSING EVIDENCE-BASED PRACTICE, THIRD EDITION: MODEL & GUIDELINES


Author: Deborah Dang,Sandra L. Dearholt
Publisher: Sigma Theta Tau
ISBN: 194044697X
Category: Medical
Page: 360
View: 1915
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Johns Hopkins Nursing Evidence-Based Practice: Model and Guidelines has proven to be one of the most foundational books on EBP in nursing. This fully revised third edition builds on the strength of the first two editions with updated content based on more than a decade of the model’s use and refinement in real-life settings. Authors Deborah Dang and Sandra L. Dearholt also incorporated feedback from nurses around the world. Key features of the Johns Hopkins Nursing EBP model include: · NEW: Tips for using the newly updated Johns Hopkins Nursing EBP model and guidelines · NEW: Tips on seeking funding for the advancement of interprofessional collaboration and teamwork · NEW: Tools to guide the EBP process, such as Stakeholder Analysis, Action Planning, and Dissemination · Explanation of the Practice question, Evidence, and Translation (PET) approach to EBP projects · Overview of the Patient, Intervention, Comparison, and Outcome (PICO) approach to EBP question development · Creation of a supportive infrastructure for building an EBP nursing environment · Exemplars detailing real-world EBP experiences CNOs, nurse managers, bedside nurses, and students alike have successfully transformed their practices and improved patient care using Johns Hopkins Nursing Evidence-Based Practice: Model and Guidelines

Hansen Solubility Parameters

A User's Handbook, Second Edition
Author: Charles M. Hansen
Publisher: CRC Press
ISBN: 9781420006834
Category: Science
Page: 544
View: 1840
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Hansen solubility parameters (HSPs) are used to predict molecular affinities, solubility, and solubility-related phenomena. Revised and updated throughout, Hansen Solubility Parameters: A User's Handbook, Second Edition features the three Hansen solubility parameters for over 1200 chemicals and correlations for over 400 materials including polymers, inorganic salts, and biological materials. To update his groundbreaking handbook with the latest advances and perspectives, Charles M. Hansen has invited five renowned experts to share their work, theories, and practical applications involving HSPs. New discussions include a new statistical thermodynamics approach for confirming existing HSPs and how they fit into other thermodynamic theories for polymer solutions. Entirely new chapters examine the prediction of environmental stress cracking as well as absorption and diffusion in polymers. Highlighting recent findings on interactions with DNA, the treatment of biological materials also includes skin tissue, proteins, natural fibers, and cholesterol. The book also covers the latest applications of HSPs, such as ozone-safe “designer” solvents, protective clothing, drug delivery systems, and petroleum applications. Presenting a comprehensive survey of the theoretical and practical aspects of HSPs, Hansen Solubility Parameters, Second Edition concludes with a detailed discussion on the necessary research, future directions, and potential applications for which HSPs can provide a useful means of prediction in areas such as biological materials, controlled release applications, nanotechnology, and self-assembly.

Fundamentals of Multimedia


Author: Ze-Nian Li,Mark S. Drew,Jiangchuan Liu
Publisher: Springer Science & Business Media
ISBN: 331905290X
Category: Computers
Page: 727
View: 2501
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This textbook introduces the “Fundamentals of Multimedia”, addressing real issues commonly faced in the workplace. The essential concepts are explained in a practical way to enable students to apply their existing skills to address problems in multimedia. Fully revised and updated, this new edition now includes coverage of such topics as 3D TV, social networks, high-efficiency video compression and conferencing, wireless and mobile networks, and their attendant technologies. Features: presents an overview of the key concepts in multimedia, including color science; reviews lossless and lossy compression methods for image, video and audio data; examines the demands placed by multimedia communications on wired and wireless networks; discusses the impact of social media and cloud computing on information sharing and on multimedia content search and retrieval; includes study exercises at the end of each chapter; provides supplementary resources for both students and instructors at an associated website.

Content Analysis

An Introduction to Its Methodology
Author: Klaus Krippendorff
Publisher: SAGE
ISBN: 1412983150
Category: Language Arts & Disciplines
Page: 441
View: 2530
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Since the publication of the first edition of Content Analysis: An Introduction to Its Methodology, the textual fabric in which contemporary society functions has undergone a radical transformation: specifically, the ongoing information revolution. Today, content analysis has become an efficient alternative to public opinion research—a method of tracking markets, political leanings, and emerging ideas, a way to settle legal disputes, and an approach to explore individual human minds.

An Introduction to Statistical Learning

with Applications in R
Author: Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
Publisher: Springer Science & Business Media
ISBN: 1461471389
Category: Mathematics
Page: 426
View: 9105
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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.