13. Stochastic Dynamical Systems
Full list of references in Chapter 13 of the IPython Cookbook, the definitive guide to high-performance scientific computing and data science in Python, by Dr. Cyrille Rossant, Packt Publishing, 400 pages, 2014.
- Stochastic differential equations.
- The white noise, derivative of the Brownian motion.
- The Langevin equation.
- The Ornstein-Uhlenbeck process is solution of the Langevin equation.
- Diffusion processes (generalization of the Ornstein-Uhlenbeck process).
- Itô calculus generalizes differential calculus to stochastic processes.
- The Euler-Maruyama method is a simple numerical method for simulating diffusion processes.