Research Repository

Dynamically sampled multivariate empirical mode decomposition

Rehman, N and Naveed, K and Safdar, MW and Ehsan, S and McDonald-Maier, KD (2015) 'Dynamically sampled multivariate empirical mode decomposition.' Electronics Letters, 51 (24). 2049 - 2051. ISSN 0013-5194

Full text not available from this repository.


© 2015 The Institution of Engineering and Technology. A method for accurate multivariate local mean estimation in the multivariate empirical mode decomposition algorithm by using a statistical data-driven approach based on the Menger curvature measure and normal-to-anything variate-generation method is proposed. This is achieved by aligning the projection vectors in the direction of the maximum 'activity' of the input signal by considering the local curvature of the signal in multidimensional spaces, resulting in accurate mean estimation even for a very small number of projection vectors.

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 12 Feb 2016 11:35
Last Modified: 22 Jan 2019 22:15

Actions (login required)

View Item View Item