Supercomputation In Nonlinear And Disordered Systems Algorithms Applications And Architectures
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Supercomputation In Nonlinear And Disordered Systems: Algorithms, Applications And Architectures
This proceedings volume is devoted to simulation and parallel computing related to nonlinear problems. One of its fundamental aims is the study of how the efforts of computer and computational scientists may be combined to develop most modern simulation environments of nonlinear systems.
Supercomputation in Nonlinear and Disordered Systems
Author: Luis Vázquez
language: en
Publisher: World Scientific Publishing Company Incorporated
Release Date: 1997
Comprises 12 contributions from the September 1996 conference. Among the paper topics: multilevel first-order system least squares methodology, HPC in industrial simulation and design, iterative and direct sparse solvers on parallel computers, nonlinear equations in the molecular theory of fluids, and issues of non-linear dynamics in the LHC. No index. Annotation copyrighted by Book News, Inc., Portland, OR
Extracting Knowledge From Time Series
Author: Boris P. Bezruchko
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-09-03
Mathematical modelling is ubiquitous. Almost every book in exact science touches on mathematical models of a certain class of phenomena, on more or less speci?c approaches to construction and investigation of models, on their applications, etc. As many textbooks with similar titles, Part I of our book is devoted to general qu- tions of modelling. Part II re?ects our professional interests as physicists who spent much time to investigations in the ?eld of non-linear dynamics and mathematical modelling from discrete sequences of experimental measurements (time series). The latter direction of research is known for a long time as “system identi?cation” in the framework of mathematical statistics and automatic control theory. It has its roots in the problem of approximating experimental data points on a plane with a smooth curve. Currently, researchers aim at the description of complex behaviour (irregular, chaotic, non-stationary and noise-corrupted signals which are typical of real-world objects and phenomena) with relatively simple non-linear differential or difference model equations rather than with cumbersome explicit functions of time. In the second half of the twentieth century, it has become clear that such equations of a s- ?ciently low order can exhibit non-trivial solutions that promise suf?ciently simple modelling of complex processes; according to the concepts of non-linear dynamics, chaotic regimes can be demonstrated already by a third-order non-linear ordinary differential equation, while complex behaviour in a linear model can be induced either by random in?uence (noise) or by a very high order of equations.