Accession Number:

ADA582418

Title:

Compact Empirical Mode Decomposition: An Algorithm to Reduce Mode Mixing, End Effect, and Detrend Uncertainty

Descriptive Note:

Journal article

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA NAVAL OCEAN ANALYSIS AND PREDICTION LAB

Personal Author(s):

• Chu, Peter C.
• Fan, Chenwu
• Huang, Norden

Report Date:

2012-01-01

Pagination or Media Count:

19.0

Abstract:

A compact empirical mode decomposition CEMD is presented to reduce mode mixing, end effect, and detrend uncertainty in analysis of time series with N data points. This new approach consists of two parts a highest-frequency sampling HFS to generate pseudo extrema for effective identification of upper and lower envelopes, and b a set of 2N algebraic equations for determining the maximum minimum envelope at each decomposition step. Among the 2N algebraic equations, 2N-2 equations are derived on the base of the compact difference concepts using the Hermitan polynomials with the values and first derivatives at the N-2 non-end points. At each end point, zero third derivative and determination of the first derivative from several odd number nearest original and pseudo extrema provide two extra algebraic equations for the value and first derivative at that end point. With this well-posed mathematical system, one can reduce the mode mixing, end effect, and detrend uncertainty drastically, and separate scales naturally without any a priori subjective criterion selection.

Descriptors:

• *TIME SERIES ANALYSIS
• DERIVATIVES(MATHEMATICS)
• POLYNOMIALS

Subject Categories:

• Numerical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE