Computational Methods for Modeling of Nonlinear Systems
Contributors: Howlett, Phil
Publisher: Elsevier Science & Technology
Published: 1974
Place of publication: Burlington
Language: eng
Format: [electronic resource]
Number of pages: 289
ISBN-13: 9780080956176
Subjects: Mathematics; Stochastic integral equations
Description: In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank mat.
Notes: Description based on print version record.
Table of contents: title: Front Cover; Random Integral Equations With Applications to Life Sciences and Engineering; Copyright Page; Contents; Preface; General Introduction; Chapter I. Preliminaries and Formulation of the Stochastic Equations; Chapter II. Some Random Integral Equations of the Volterra Type with Applications; Chapter III. Approximate Solution of the Random Volterra Integral Equation and an Application to Population Growth Modeling; Chapter IV. A Stochastic Integral Equation of the Fredholm Type and Some Applications; Chapter V. Random Discrete Fredholm and Volterra Systems.; title: Chapter VI. Nonlinear Perturbed Random Integral Equations and Application to Biological SystemsChapter VII. On a Nonlinear Random Integral Equation with Application to Stochastic Chemical Kinetics; Chapter VIII. Stochastic Integral Equations of the Ito Type; Chapter IX. Stochastic Nonlinear Differential Systems; Chapter X. Stochastic Integrodifferential Systems; Bibliography; Index.