Time-Frequency analysis for nonlinear and non-stationary signals using HHT: A mode mixing separation technique

DOI

https://doi.org/10.1109/TLA.2018.8362142

Document Type

Article

Publication Date

4-1-2018

Publication Title

IEEE Latin America Transactions

Abstract

Time and frequency localizations are of crucial importance in the analysis of nonlinear and non-stationary processes, especially in systems with high level of complexity where detection of information/events, estimation of parameters and classification of signals in classes is necessary to take decisions. The Hilbert Huang Transform (HHT) offers an adaptive approach to analyze no-linear and non-stationary processes. This paper exposes the HHT approach and its new methodologies for improvement of the analysis, such as the masking process. Two examples are given to show the techniques, first a synthetic signal, representing a typical behavior of an electrical signal immersed in a power electronic environment and second a brain signal to extend the acknowledgment to a biological process. Finally a mode mixing separation technique is presented.

Volume

16

Issue

4

First Page

1091

Last Page

1098

ISSN

15480992

Identifier

SCOPUS_ID:85048228171

Documento original

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