UID:
almahu_9949697762602882
Format:
1 online resource (289 p.)
ISBN:
1-283-52588-7
,
9786613838339
,
0-08-095617-3
Series Statement:
Mathematics in science and engineering ; v. 108
Content:
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
Note:
Description based upon print version of record.
,
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; 1.0 Introduction; 1.1 Basic Definitions and Theorems from Functional Analysis; 1.2 Probabilistic Definitions; 1.3 The Stochastic Integral Equations and Stochastic Differential Systems; Appendix 1.A; Chapter II. Some Random Integral Equations of the Volterra Type with Applications; 2.0 Introduction; 2.1 The Random Integral Equation; 2.2 Some Applications of the Equation
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2.3 The Random Integral Equation2.4 Applications of the Integral Equation; Chapter III. Approximate Solution of the Random Volterra Integral Equation and an Application to Population Growth Modeling; 3.0 Introduction; 3.1 The Method of Successive Approximations; 3.2 A New Stochastic Formulation of a Population Growth Problem; 3.3 Method of Stochastic Approximation; Chapter IV. A Stochastic Integral Equation of the Fredholm Type and Some Applications; 4.0 Introduction; 4.1 Existence and Uniqueness of a Random Solution; 4.2 Some Special Cases
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4.3 Stochastic Asymptotic Stability of the Random Solution4.4 An Application in Stochastic Control Systems; 4.5 A Random Perturbed Fredholm Integral Equation; Chapter V. Random Discrete Fredholm and Volterra Systems; 5.0 Introduction; 5.1 Existence and Uniqueness of a Random Solution of System (5.0.1); 5.2 Special Cases of Theorem 5.1.2; 5.3 Stochastic Stability of the Random Solution; 5.4 An Approximation to System (5.0.1 ); 5.5 Application to Stochastic Control Systems; Chapter VI. Nonlinear Perturbed Random Integral Equations and Application to Biological Systems; 6.0 Introduction
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6.1 The Random Integral Equation6.2 Applications to Biological Systems; Chapter VII. On a Nonlinear Random Integral Equation with Application to Stochastic Chemical Kinetics; 7.0 Introduction; 7.1 Mathematical Preliminaries; 7.2 An Existence and Uniqueness Theorem; 7.3 A Stochastic Chemical Kinetics Model; Chapter VIII. Stochastic Integral Equations of the Ito Type; 8.0 Introduction; 8.1 Preliminary Remarks; 8.2 On an Ito Stochastic Integral Equation; 8.3 On Ito-Doob-Type Stochastic Integral Equations; Chapter IX. Stochastic Nonlinear Differential Systems; 9.0 Introduction
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9.1 Reduction of the Stochastic Differential Systems9.2 Stochastic Absolute Stability of the Differential Systems; Appendix 9.A; Chapter X. Stochastic Integrodifferential Systems; 10.0 Introduction; 10.1 The Stochastic Integrodifferential Equation; 10.2 Reduction of the Stochastic Nonlinear Integrodifferential Systems with Time Lag; 10.3 Stochastic Absolute Stability of the Systems; Bibliography; Index
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English
Additional Edition:
ISBN 0-12-702150-7
Language:
English
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