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Title: An enhance empirical mode decomposition Authors:  Gareth Peters - University College London (United Kingdom)
Nourddine Azzaoui - Universite Clermont Auvergne (France)
Tomoko Matsui - The Institute of Statistical Mathematics (Japan)
Marta Campi - University College London (United Kingdom) [presenting]
Abstract: A new technique, called Enhanced Empirical Mode Decomposition (EEMD), will be presented. Firstly, we introduce which are the classical a-priori decomposition basis techniques within the literature such as the Fourier Transform, the Wavelet Transform. Afterwards, the classical Empirical Mode Decomposition is presented. We will then underline pros and cons of it by paying particular attention to its drawbacks and so highlighting the motivation behind my new technique. Afterwards, a finance application comparing the EMD and the EEMD is provided in order to present its main advantages.