TC 1.4. Stochastic Systems

Stochastic Systems is an area of systems theory that deals with dynamic as well as static systems, which can be characterized by stochastic processes, stationary or non-stationary, or by spectral measures. Stochastic Systems arise in various disciplines within engineering and science, such as control, communications and networks, signal processing, biology and finance. Some key applications include communication system design for both wired and wireless systems, gene sequencing and analysis, and biological system modelling, financial data modelling and forecasting, econometrics, environmental modelling and forecasting, and many others. Many of the models employed within the framework of stochastic systems originated in an attempt to quantify in a rigorous way the treatment of probabilistic modelling and inference, random dynamical systems, and information; they often build on the axiomatic approach to probability of Kolmogorov, the random noise model of Wiener and the information measure of Shannon.

Welcome Message from the Chair

If you are a researcher and your interests include Stochastic Systems, in particular, stochastic modelling, identification, estimation and control for time-series data as well as dynamical systems, then this Technical Committee is for you.

If you are a practitioner working with automatic control systems, communications and networks, signal processing, biology and finance then Stochastic Systems modelling, analysis and design are probably the reality you deal with every day.