For more information about this meeting, contact Hope Shaffer, Chun Liu.
|Title:||Data driven methods for dynamical systems: Extracting spatiotemporal patterns from high-dimensional time series|
|Seminar:||CCMA Luncheon Seminar|
|Speaker:||Dimitrios Giannakis, New York University (Host: J Harlim)|
|Large-scale datasets generated by dynamical systems arise in many applications in science and engineering. A research topic of current interest in this area involves using data collected through observational networks or output by numerical models to extract the salient modes of variability from high-dimensional data, and create low-order models to forecast these modes. In this talk we discuss applied mathematics techniques to address this topic blending ideas from machine learning, harmonic analysis, and delay-coordinate embeddings of dynamical systems. We illustrate these techniques with applications to climate atmosphere ocean science.|
Room Reservation Information
|Date:||10 / 06 / 2014|
|Time:||12:20pm - 01:30pm|