System Parameter Identification

Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification. The authors’ research provides a base for the book, but it incorporates the results from the latest international research publications. Named a 2013 Notable Computer Book for Information Systems by Computing Reviews One of the first books to present system parameter identification with information theoretic criteria so readers can track the latest developments Contains numerous illustrative examples to help the reader grasp basic methods

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  • Author : Badong Chen
  • Publisher : Newnes
  • Pages : 266 pages
  • ISBN : 0124045952
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKSystem Parameter Identification

System Parameter Identification

System Parameter Identification
  • Author : Badong Chen,Yu Zhu,Jinchun Hu,Jose C. Principe
  • Publisher : Newnes
  • Release : 17 July 2013
GET THIS BOOKSystem Parameter Identification

Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification. The authors’ research provides a base

Nonlinear System Identification — Input-Output Modeling Approach

Nonlinear System Identification — Input-Output Modeling Approach
  • Author : Robert Haber,L. Keviczky
  • Publisher : Springer
  • Release : 22 December 2012
GET THIS BOOKNonlinear System Identification — Input-Output Modeling Approach

The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of

Parameter Identification and Monitoring of Mechanical Systems Under Nonlinear Vibration

Parameter Identification and Monitoring of Mechanical Systems Under Nonlinear Vibration
  • Author : Juan Carlos A. Jauregui Correa
  • Publisher : Elsevier
  • Release : 11 December 2014
GET THIS BOOKParameter Identification and Monitoring of Mechanical Systems Under Nonlinear Vibration

Development of new sensors and digital processors has provided opportunity for identification of nonlinear systems. Vibration measurements have become standard for predicting and monitoring machinery in industry. Parameter Identification and Monitoring of Mechanical Systems under Nonlinear Vibration focusses on methods for the identification of nonlinearities in mechanical systems, giving description and examples of practical application. Chapters cover nonlinear dynamics; nonlinear vibrations; signal processing; parameter identification; application of signal processing to mechanical systems; practical experience and industrial applications; and synchronization of

Nonlinear System Identification: Nonlinear system parameter identification

Nonlinear System Identification: Nonlinear system parameter identification
  • Author : Robert Haber,László Keviczky
  • Publisher : Springer Science & Business Media
  • Release : 18 September 1999
GET THIS BOOKNonlinear System Identification: Nonlinear system parameter identification

The first of two volumes, this handbook presents a comprehensive overview of nonlinear dynamic system parameter identification. The volumes cover many aspects of nonlinear processes including modelling, parameter estimation, structure search, nonlinearity and model validity tests.

Optimal Measurement Methods for Distributed Parameter System Identification

Optimal Measurement Methods for Distributed Parameter System Identification
  • Author : Dariusz Ucinski
  • Publisher : CRC Press
  • Release : 27 August 2004
GET THIS BOOKOptimal Measurement Methods for Distributed Parameter System Identification

For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software systems. With the expense of scanning and moving sensors, optimal placement presents a critical problem.

Mathematical and Computational Modeling and Simulation

Mathematical and Computational Modeling and Simulation
  • Author : Dietmar P.F. Möller
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKMathematical and Computational Modeling and Simulation

This introduction and textbook familiarizes engineers with the use of mathematical and computational modeling and simulation in a way that develops their understanding of the solution characteristics of a broad class of real-world problems. The relevant basic and advanced methodologies are explained in detail, with special emphasis on ill-defined problems. Some fifteen simulation systems are presented on the language and the logical level. Moreover, the reader also can accumulate an experiential overview by studying the wide variety of case studies

Nonlinear System Identification — Input-Output Modeling Approach

Nonlinear System Identification — Input-Output Modeling Approach
  • Author : Robert Haber,L. Keviczky
  • Publisher : Springer
  • Release : 31 July 1999
GET THIS BOOKNonlinear System Identification — Input-Output Modeling Approach

The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of

Identification of Dynamic Systems

Identification of Dynamic Systems
  • Author : Rolf Isermann,Marco Münchhof
  • Publisher : Springer Science & Business Media
  • Release : 22 November 2010
GET THIS BOOKIdentification of Dynamic Systems

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods

System Identification

System Identification
  • Author : Rik Pintelon,Johan Schoukens
  • Publisher : John Wiley & Sons
  • Release : 05 April 2004
GET THIS BOOKSystem Identification

Electrical Engineering System Identification A Frequency DomainApproach How does one model a linear dynamic system from noisydata? This book presents a general approach to this problem, withboth practical examples and theoretical discussions that give thereader a sound understanding of the subject and of the pitfallsthat might occur on the road from raw data to validated model. Theemphasis is on robust methods that can be used with a minimum ofuser interaction. Readers in many fields of engineering will gainknowledge about: * Choice