Date of Award


Document Type


Degree Name

Master of Science


Department of Electrical and Computer Engineering

First Advisor

Andrew J. Terzuoli, PhD.


A review of current signal analysis tools show that new techniques are required for an enhanced fidelity or data integrity. Recently, the Hilbert-Huang transform (HHT) and its inherent property, the Empirical Mode Decomposition (EMD) technique, have been formerly investigated. The technique of Complex EMD (CEMD) was also explored. The scope of this work was to assess the CEMD technique as an innovative analysis tool. Subsequent to this, comparisons between applications of the Hilbert transform (HT) and the Fast-Fourier transform (FFT) were analyzed. MATLAB was implemented to model signal decomposition and the execution of mathematical transforms for generating results. The CEMD technique successfully decomposed the data into its oscillatory modes. After comparative graphical analysis of the HT and FFT, application of the HT provided marginal enhancements of the data modeled previously by the FFT. Altogether, the HHT could not be determined as a helpful analysis tool. Nevertheless, the CEMD technique, an inherent component of the HHT, exhibited a possible improvement as an analysis tool for signal processing data. Further evaluation of the CEMD technique and the HHT is needed for ultimate determination of their usefulness as an analysis tool.

AFIT Designator


DTIC Accession Number