Stochastic differential equations (SDEs) and random processes form a central framework for modelling systems influenced by inherent uncertainties. These mathematical constructs are used to rigorously ...

Applications range from medical imaging to autonomous vehicle technology. Learn data manipulation techniques to improve signal or image fidelity. Understand the theory of probability and stochastic ...

Random walks constitute one of the most fundamental models in the study of stochastic processes, representing systems that evolve in a sequence of random steps. Their applications range from modelling ...

CATALOG DESCRIPTION: Advanced topics in random processes: point processes, Wiener processes; Markov processes, spectral representation, series expansion of random processes, linear filtering, Wiener ...

Ivan Bajic (ibajic at ensc.sfu.ca) Office hours: Monday and Wednesday, 13:00-14:00 online (Zoom, see the link in course materials) Introduction to the theories of probability and random variables, and ...

The equilibrium rate rY of a random variable Y with support on non-negative integers is defined by rY(0)=0 and rY(n)=P[Y=n-1]/P[Y=n],(n≥ 1). Let Yj (i),(j=1,⋯ ,m ...

We give necessary and sufficient conditions for $P(\sum{_{n=1}^{\infty}}(A + S_{n})^{-1} < \infty) = 1$ in terms of E(∑n=1 ∞(A + Sn)-1), where Sn is the sum of n ...

French mathematician and astronomer, Pierre-Simon Laplace brought forth the first major treatise on probability that combined calculus and probability theory in 1812. A single roll of the dice can be ...

This project aims at developing mathematical statistics and probability theory to provide methodologies for modeling and analysis of complex random systems. Statistical methods enable analysis of ...