书目名称 | Dynamic Systems Models |
副标题 | New Methods of Param |
编辑 | Josif A. Boguslavskiy,Mark Borodovsky |
视频video | |
概述 | 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 |
图书封面 |  |
描述 | This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics..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 Mo |
出版日期 | Book 2016 |
关键词 | Aerospatial Dynamics; Assest Pricing; Biological Sequence Analysis; Hidden Markov Model; Inverse Problem |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-319-04036-3 |
isbn_softcover | 978-3-319-79141-8 |
isbn_ebook | 978-3-319-04036-3 |
copyright | Springer International Publishing Switzerland 2016 |