Because probability and statistics are as much about intuition and problem solving, as they are about theorem proving, students can find it very difficult to make a successful transition from lectures to examinations and practice. Since the subject is critical in many modern applications, Yuri Suhov
Random Integral Equations with Applications to Life Sciences and Engineering
โ Scribed by Chris P. Tsokos and W.J. Padgett (Eds.)
- Publisher
- Elsevier Science
- Year
- 1974
- Tongue
- English
- Leaves
- 289
- Series
- Mathematics in Science and Engineering 108
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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 matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; andmethods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory.As a result, the book represents a blend of new methods in general computational analysis,and specific, but also generic, techniques for study of systems theory ant its particularbranches, such as optimal filtering and information compression. - Best operator approximation,- Non-Lagrange interpolation,- Generic Karhunen-Loeve transform- Generalised low-rank matrix approximation- Optimal data compression- Optimal nonlinear filtering
โฆ Table of Contents
Content:
Dedication
Page ii
Edited by
Page iii
copyright page
Page iv
Preface
Pages ix-x
General Introduction
Pages 1-5
Chapter I Preliminaries and Formulution of the Stochastic Equations
Pages 6-28
Chapter II Some Random Integral Equations of the Volterra Type with Applications
Pages 29-64
Chapter III Approximate Solution of the Random Volterra Integral Equation and an Application to Population Growth Modeling
Pages 65-96
Chapter IV A Stochastic Integal Equalation of the Fredholm Type and Some Applications
Pages 97-131
Chapter V Random Discrete Fredholm and Volterra Systems
Pages 132-155
Chapter VI Nonlinear Perturbed Random Integral Equations and Application to Biological Systems
Pages 156-179
Chapter VII On a Nonlinear Random Integral Equation with App lication to Stochastic Chemical Kinetics
Pages 180-206
Chapter VIII Stochastic Integral Equations Of the Ito Type
Pages 207-216
Chapter IX Stochastic Nonlinear Differential Systems
Pages 217-240
Chapter X Stochastic Integrodifferential Systems
Pages 241-259
Bibliography
Pages 260-273
Index
Pages 275-278
๐ SIMILAR VOLUMES
<span>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-L