Content, progress and pedagogy of the module

Learning objectives

Knowledge

• Can describe stochastic processes and their applications as models of real signals
• Can explain the defining properties of different stationary stochastic process models

Skills

• Can select analytical tools for studying the phenomenon of chance in an engineering context
• Can analyse and characterise stochastic phenomena and choose appropriate models
• Can demonstrate understanding of concepts, theories and techniques for estimating parameters in discrete stochastic processes
• Can apply cross- and auto-correlation for analysing stochastic processes
• Can estimate the power spectral density of discrete stochastic processes and understand the limitations of this estimate
• Can analyse biomedical signals, which can be modelled as stochastic processes using power spectrum density

Type of instruction

The module is taught, cf. §17 of the study programme

Exam

Exams