Firas Khasawneh ME Faculty Candidate - Research Seminar
- Monday, February 13, 2017 at 10:00am
- Roberts Hall, Room 321 - view map
Utilizing Topology to Investigate Signals of Noisy Systems With Time Delays
Abstract: Recent advances in sensor technology and computer hardware has led to a shift towards data-driven analysis and modeling of engineered and natural systems. The datasets are obtained through either numerical simulations or experiments and often contain complex dynamics hidden in some high-dimensional structure. The analysis of these systems becomes even more challenging in the presence of time delays, which can be either inherent to the physical process or introduced in order to capture the lag in transmission or processing. Therefore, there is a need for new investigative tools that will enable studying models of systems with delays as well as the direct signals of dynamic systems.
This talk will discuss an innovative framework for time series analysis through advancing and linking signal processing, dynamical systems, and applied topology. Current literature on time series analysis aims to study the underlying structure of dynamic systems by searching for a lower dimensional representation; however, the need for user-defined inputs, the sensitivity of these inputs to error, and the expensive computational effort limit the usability of available knowledge, especially for in-situ signal analysis. We will also discuss the added complexity of time delays and noise in the system model, and show numerical and pseudo-analytical methods to extract information on an example model from machining dynamics.