This is a preview. Log in through your library . Abstract We consider a discrete time hidden Markov model where the signal is a stationary Markov chain. When conditioned on the observations, the ...

CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...

A critical branching process {Zk, k = 0, 1, 2,...} in a random environment is considered. A conditional functional limit theorem for the properly scaled process {log Zpu, 0 ≤ u < ∞} is established ...

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 ...

This course is compulsory on the BSc in Mathematics, Statistics and Business. This course is available on the BSc in Data Science, BSc in Mathematics with Data Science, Erasmus Reciprocal Programme of ...

Conditional probability occurs when it is given that something has happened. (Hint: look for the word “given” in the question. The probability that a tennis player wins the first set of a match is ...

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