Stochastic Process

Course description and objectives

This course devotes to advanced topics on the Stochastic process and data analysis for graduate students.

References:

  • The Fokker Plank Equation, H. Risken, Springer 1989
  • Random Vibration, D. E. Newland, 1997
  • Stochastic Processes for Physicists, K. Jacobs, Cambridge 2010

Some topics are as follows:

  • Introduction to the Probability distributions
  • Correlation function
  • Spectral Density
  • Fractals
  • R/S & MF-DFA
  • Random Matrix Theory
  • Markov Process
  • Langevin Equation
  • Fokker Plank Equation
  • Complex Networks

Lecture notes

Part0

Part I

Part II …… Sample1 Data Download —– Exercise 1: (Saeedeh, Sina Ghafouri, Amirhossein Pilehvarian, Ahmad Babadi)

Part III

Part IV …… Sample2 data Download —– Exercise 2:

Part V

Part VI

Part VII

Part VIII