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DifferentiAlequations are powerful tools to model the time evolution of dynamical
systems, which have arisen widely in mechanics, physics, biology, ecology and the other
scientific fields. In the reAlworld, dynamicAlsystems are usually in?uenced by delay phe-
nomenon or random perturbation. Therefore, differentiAlequations containing these factors
can better simulate the reAldynamicAlsystems. However, the increasing complexity of
equations makes it almost impossible to get their explicit solutions, and hard to study their
dynamicAlproperties. Thus, it is of great significance to develop numericAlmethods for
solving these differentiAlequations, and analyze the properties of numericAlsolutions, such
as convergence and stability. In this thesis, we focus on severAltypes of differentiAlequa-
tions including stochastic and delay arguments, develop one-step methods for solving these
equations, and study the convergence and stability of these methods.
In chapter 2, by combining the idea of split-step methods with stochastic θ-methods, we
propose a class of split-step θ-methods for solving stochastic delay differentiAlequations. It
is proved that the methods are convergent with strong order 0.5 in the mean-square sense.
Chapter 3 is devoted to study the index-1stochastic delay differential-algebraic equa-
tions (SDDAEs) of retarded type. The existence and uniqueness of strong solutions are
derived under uniform Lipschitz condition and some generAlassumptions.
In chapter 4, we develop a generAlframework for a class of one-step methods for
solving index-1SDDAEs of retarded type, and establish the strong convergence criterion.
Based on the criterion, we construct some specific schemes for solving index-1SDDAEs of
retarded type and semi-explicit stochastic differential-algebraic equations of index-1.
In chapter 5, by adapting the existed numericAlmethods of ordinary differentiAlequa-
tions, a class of extended Rosenbrock numericAlsimulation methods for solving discrete-
distributed delay systems of neutrAltype are constructed, and some criteria, for judging
that the numericAlmethods are asymptotically stable, are obtained. It is shown that meth-
ods extended from A-stable classicAlRosenbrock methods can preserve the asymptotically
stability of the underlying linear system.
In chapter 6, for a class of nonlinear functional-integro-differentiAlequations, a type
of mixed Runge-Kutta methods are presented by combining the underlying Runge-Kutta
methods and the compound quadrature rules. Based on the non-classicAlLipschitz condi-
tion, some globAland asymptoticAlstability criteria are derived for the methods. Several
specific mixed Runge-Kutta methods of high precision and good stability are derived.
With numericAlexperiments, efficiency of the proposed methods and applicability of
the theoreticAlresults are further illustrated.