Plenary Lecture

Towards the Optimum Sensing and Modeling of Complex Systems

Professor Pavel Loskot
Systems and Process Engineering Centre
College of Engineering
Swansea University
United Kingdom

Abstract: Mathematical modeling of stochastic systems is becoming immensely attractive in order to provide new insights or designs for these systems. One strategy is to collect a lot of data about a system of interest with the hope that some of these data will be useful in building the model. In this case, the model application dictates which data are relevant and which data can be ignored. This strategy is usually followed for the systems where there is prior uncertainty about the model application. More efficient data collection strategy defines the model application first in order to specify which data are required to at least partially constrain the model. For complex systems, combining both strategies is likely to be the best approach. In this talk, we will try to formalize these two strategies to define the optimum tasks of data collection and system modeling.

Brief Biography of the Speaker: Pavel Loskot has been with Swansea University in the UK since 2007. He also held research contracts with various institutions and companies around the world. In his career, he was involved in a broad range of diverse projects where he created and subsequently analyzed various models concerning telecommunication systems, biological systems and even air transport networks. His main expertise as well as the current research interest is in the area of statistical and digital signal processing and software development.

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