๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Random Integral Equations with Applications to Life Sciences and Engineering

โœ 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

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ 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

โœฆ 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


๐Ÿ“œ SIMILAR VOLUMES


Random integral equations with applicati
โœ Anatoli Torokhti; Phil Howlett ๐Ÿ“‚ Library ๐Ÿ“… 1974 ๐Ÿ› Elsevier Science & Technology ๐ŸŒ English

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 Applicati
โœ Chris P. Tsokos, W.J. Padgett ๐Ÿ“‚ Library ๐Ÿ“… 1974 ๐Ÿ› Academic Press ๐ŸŒ English

<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