Contents《生物数学丛书》序PrefaceChapter 1 Introduction 11.1 Introduction 11.2 Basic notations of probability theory 21.3 Stochastic processes 91.4 Brownian motions 151.5 Stochastic integrals 181.6 It?o’s formula 311.7 Moment inequalities 401.8 Gronwall-type inequalities 45Chapter 2 Existence, uniqueness and exponential stability for stochastic age-dependent population 482.1 Introduction 482.2 Assumptions and preliminaries 492.3 Existence and uniqueness of solutions 522.3.1 Uniqueness of solutions 522.3.2 Existence of strong solutions 532.4 Stability of strong solutions 59Chapter 3 Existence and uniqueness for stochastic age-structured population system with diffusion 643.1 Introduction 643.2 Euler approximation and main result 663.3 Existence and uniqueness of solutions 683.3.1 Uniqueness of solutions 683.3.2 Existence of strong solutions 703.4 Numerical simulation example 76Chapter 4 Existence and uniqueness for stochastic age-dependent population with fractional Brownian motion 794.1 Introduction 794.2 Preliminaries 814.3 Existence and uniqueness of solutions 84Chapter 5 Convergence of the Euler scheme for stochastic functional partial differential equations 905.1 Introduction 905.2 Preliminaries and the Euler approximation 915.3 The main results 935.4 Numerical simulation example 99Chapter 6 Numerical analysis for stochastic age-dependent population equations 1016.1 Introduction 1016.2 Preliminaries and the Euler approximation 1026.3 The main results 105Chapter 7 Convergence of numerical solutions to stochastic age-structured population system with diffusion 1167.1 Introduction 1167.2 Preliminaries and approximation 1187.3 The main results 1217.4 Numerical simulation example 126Chapter 8 Exponential stability of numerical solutions to a stochastic age-structured population system with diffusion 1288.1 Introduction 1288.2 Preliminaries and Euler approximation 1308.3 The main results 1328.4 Numerical simulation example 137Chapter 9 Numerical analysis for stochastic age-dependent population equations with fractional Brownian motion 1409.1 Introduction 1409.2 Preliminaries and the Euler approximation 1419.3 The main results 1449.4 Numerical simulation example 154Chapter 10 Convergence of the semi-implicit Euler method for stochastic age-dependent population equations with Markovian switching 15610.1 Introduction 15610.2 Preliminaries and semi-implicit approximation 15710.3 Several lemmas 15910.4 Main results 165Chapter 11 Convergence of numerical solutions to stochastic age-dependent population equations with Poisson jump and Markovian switching 17011.1 Introduction 17011.2 Preliminaries and semi-implicit approximation 17111.3 Several lemmas 17311.4 Main results 179Chapter 12 Numerical analysis for stochastic delay neural networks with Poisson jump 18412.1 Introduction 18412.2 Preliminaries and the Euler approximation 18512.3 The main results 18712.4 Numerical simulation example 195Chapter 13 Convergence of numerical solutions to stochastic delay neural networks with Poisson jump and Markov switching 19713.1 Introduction 19713.2 Preliminaries and the Euler approximation 19813.3 Lemmas and corollaries 20113.4 Convergence with the local Lipschitz condition 205Chapter 14 Exponential stability of numerical solutions to a stochastic delay neural networks 21114.1 Introduction 21114.2 Preliminaries and approximation 21214.3 Lemmas 21414.4 Numerical simulation example 220Bibliography 222Index 228