Tidal Analysis Using Time-Frequency Signal Processing and Information Clustering

• Type: Article in International Scientific Journal
• Date: 2017

Authors

António Mendes Lopes (Author) FEUP; José Tenreiro Machado (Author) Other

Journal

Title: Entropy

Vol. 19

Final page: 390

ISSN: 1099-4300

Publisher: MDPI

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 7 Citations

Other information

Authenticus ID: P-00M-YXY

DOI: 10.3390/e19080390

Abstract (EN): Geophysical time series have a complex nature that poses challenges to reaching assertive conclusions, and require advanced mathematical and computational tools to unravel embedded information. In this paper, time-frequency methods and hierarchical clustering (HC) techniques are combined for processing and visualizing tidal information. In a first phase, the raw data are pre-processed for estimating missing values and obtaining dimensionless reliable time series. In a second phase, the Jensen-Shannon divergence is adopted for measuring dissimilarities between data collected at several stations. The signals are compared in the frequency and time-frequency domains, and the HC is applied to visualize hidden relationships. In a third phase, the long-range behavior of tides is studied by means of power law functions. Numerical examples demonstrate the effectiveness of the approach when dealing with a large volume of real-world data.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 18