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Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated.
The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamics or biological sequence analysis. The technical material is illustrated by the use of worked examples and methods for training the algorithms are included.
Dynamic Systems Models provides researchers in aerospatial engineering, bioinformatics and financial mathematics (as well as computer scientists interested in any of these fields) with a reliable and effective numerical method for nonlinear estimation and solving boundary problems when carrying out control design. It will also be of interest to academic researchers studying inverse problems and their solution.
Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated.
The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamics or biological sequence analysis. The technical material is illustrated by the use of worked examples and methods for training the algorithms are included.
Dynamic Systems Models provides researchers in aerospatial engineering, bioinformatics and financial mathematics (as well as computer scientists interested in any of these fields) with a reliable and effective numerical method for nonlinear estimation and solving boundary problems when carrying out control design. It will also be of interest to academic researchers studying inverse problems and their solution.
Lays down a new method of solving inverse problems equations with weaker requirements than existing methods
Reinforces basic principles and demonstrates methodical efficiency using non-trivial applied examples
Relevant to many applications from bioinformatics through aerodynamics to financial mathematics
Includes supplementary material: [...]
From the Contents: Linear Estimators of a Random-Parameter Vector.-Basis of the Method of Polynomial Approximation.- Polynomial Approximation and Optimization of Control.- Polynomial Approximation Technique Applied to Inverse Vector Functions.- Identification of Parameters of Nonlinear Dynamical Systems: Smoothing, Filtering and Forecasting the State Vector.- Estimating Status Vectors from Sight Angles.- Estimation of Parameters of Stochastic Models.- Designing the Control of Motion to a Target Point of Phase Space.- Inverse Problems of Dynamics Algorithm for Identifying Parameters of an Aircraft
Erscheinungsjahr: | 2016 |
---|---|
Fachbereich: | Theoretische Physik |
Genre: | Physik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xx
201 S. |
ISBN-13: | 9783319040356 |
ISBN-10: | 3319040359 |
Sprache: | Englisch |
Herstellernummer: | 86317055 |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: | Boguslavskiy, Josif A. |
Redaktion: | Borodovsky, Mark |
Herausgeber: | Mark Borodovsky |
Auflage: | 1st ed. 2016 |
Hersteller: | Springer International Publishing |
Maße: | 241 x 160 x 18 mm |
Von/Mit: | Josif A. Boguslavskiy |
Erscheinungsdatum: | 30.03.2016 |
Gewicht: | 0,506 kg |
Lays down a new method of solving inverse problems equations with weaker requirements than existing methods
Reinforces basic principles and demonstrates methodical efficiency using non-trivial applied examples
Relevant to many applications from bioinformatics through aerodynamics to financial mathematics
Includes supplementary material: [...]
From the Contents: Linear Estimators of a Random-Parameter Vector.-Basis of the Method of Polynomial Approximation.- Polynomial Approximation and Optimization of Control.- Polynomial Approximation Technique Applied to Inverse Vector Functions.- Identification of Parameters of Nonlinear Dynamical Systems: Smoothing, Filtering and Forecasting the State Vector.- Estimating Status Vectors from Sight Angles.- Estimation of Parameters of Stochastic Models.- Designing the Control of Motion to a Target Point of Phase Space.- Inverse Problems of Dynamics Algorithm for Identifying Parameters of an Aircraft
Erscheinungsjahr: | 2016 |
---|---|
Fachbereich: | Theoretische Physik |
Genre: | Physik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xx
201 S. |
ISBN-13: | 9783319040356 |
ISBN-10: | 3319040359 |
Sprache: | Englisch |
Herstellernummer: | 86317055 |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: | Boguslavskiy, Josif A. |
Redaktion: | Borodovsky, Mark |
Herausgeber: | Mark Borodovsky |
Auflage: | 1st ed. 2016 |
Hersteller: | Springer International Publishing |
Maße: | 241 x 160 x 18 mm |
Von/Mit: | Josif A. Boguslavskiy |
Erscheinungsdatum: | 30.03.2016 |
Gewicht: | 0,506 kg |