Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool

Ingrid Daubechies, Jianfeng Lu, Hau Tieng Wu

Research output: Contribution to journalArticlepeer-review


The EMD algorithm is a technique that aims to decompose into their building blocks functions that are the superposition of a (reasonably) small number of components, well separated in the time-frequency plane, each of which can be viewed as approximately harmonic locally, with slowly varying amplitudes and frequencies. The EMD has already shown its usefulness in a wide range of applications including meteorology, structural stability analysis, medical studies. On the other hand, the EMD algorithm contains heuristic and ad hoc elements that make it hard to analyze mathematically. In this paper we describe a method that captures the flavor and philosophy of the EMD approach, albeit using a different approach in constructing the components. The proposed method is a combination of wavelet analysis and reallocation method. We introduce a precise mathematical definition for a class of functions that can be viewed as a superposition of a reasonably small number of approximately harmonic components, and we prove that our method does indeed succeed in decomposing arbitrary functions in this class. We provide several examples, for simulated as well as real data.

Original languageEnglish (US)
Pages (from-to)243-261
Number of pages19
JournalApplied and Computational Harmonic Analysis
Issue number2
StatePublished - Mar 2011


  • Empirical mode decomposition
  • Synchrosqueezing
  • Time-frequency analysis
  • Wavelet

ASJC Scopus subject areas

  • Applied Mathematics


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