The Theory of Stochastic Processes i

In financial and actuarial modeling and other areas of application, stochastic differential equations with jumps have been employed to describe the dynamics of various state variables. The numerical solution of such equations is more complex than that of those only driven by Wiener processes, described in Kloeden & Platen: Numerical Solution of Stochastic Differential Equations (1992).

This 3rd edition provides an insight into the mathematical crossroads formed by functional analysis (the macroscopic approach), partial differential equations (the mesoscopic approach) and probability (the microscopic approach) via the mathematics needed for the hard parts of Markov processes. It brings these three fields of analysis together, providing a comprehensive study of Markov processes from a broad perspective. The material is carefully and effectively explained, resulting in a surprisingly readable account of the subject.

Cet ouvrage propose une approche concise mais complète de la théorie de l'intégrale stochastique dans le cadre général des semimartingales continues. Après une introduction au mouvement brownien et à ses principales propriétés, les martingales et les semimartingales continues sont présentées en détail avant la construction de l'intégrale stochastique. Les outils du calcul stochastique, incluant la formule d'Itô, le théorème d'arrêt et de nombreuses applications, sont traités de manière rigoureuse.

The development of cognitive models is a key step in the challenging research program to advance our understanding of human cognition and behavior. Dynamical models represent a general and flexible approach to cognitive modeling. This introduction focuses on applications of stochastic processes and dynamical systems to model cognition.