Publication Type : Conference Paper
Thematic Areas : Center for Computational Engineering and Networking (CEN)
Publisher : IEEE
Source : 2019 International Conference on Intelligent Computing and Control Systems (ICCS), IEEE, Madurai, India (2019)
Url : https://ieeexplore.ieee.org/abstract/document/9065685
Campus : Coimbatore
School : School of Engineering
Center : Center for Computational Engineering and Networking, Computational Engineering and Networking
Department : Electronics and Communication
Year : 2019
Abstract : The unprecedented availability of data in various fields reinforces the need for more comprehensive and advanced data-driven algorithms to deal with it. The data-driven techniques are able to handle the large volume of heterogeneous data and to extract more valuable information regarding the underlying system. This paper investigates the effectiveness of modern data-driven methods for data from non-linear systems. The effectiveness of dynamic mode decomposition (DMD) and its variants such as rSVD-DMD, randomized DMD (RDMD) and total DMD (TDMD) for dta from nonlinear system is investigated. The data considered for this study are cylindrical fluid flow and neuro recordings.
Cite this Research Publication : Akshay, S., Gopalakrishnan, E. A. and Soman, K. P. “Investigating the Effectiveness of DMD and its variants for Complex Data Analysis”. International Conference on Intelligent Computing and Control Systems. May 15 – 17, 2019, Madurai, India.