Empirical Wavelet Transform
Jérôme Gilles
Abstract
Some recent methods, like the empirical mode decomposition (EMD), propose to decompose a signal accordingly to its contained information. Even though its adaptability seems useful for many applications, the main issue with this approach is its lack of theory. This paper presents a new approach to build adaptive wavelets. The main idea is to extract the different modes of a signal by designing an appropriate wavelet filter bank. This construction leads us to a new wavelet transform, called the empirical wavelet transform. Many experiments are presented showing the usefulness of this method compared to the classic EMD.
Topics & Concepts
Wavelet transformComputer scienceWaveletSignal processingArtificial intelligenceMathematicsPattern recognition (psychology)TelecommunicationsRadarMachine Fault Diagnosis TechniquesImage and Signal Denoising MethodsFault Detection and Control Systems