An improved EEMD method based on the adjustable cubic trigonometric cardinal spline interpolation |
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| Affiliation: | 1. LMIB, School of Mathematics and Systems Science, Beihang University, Beijing 100191, PR China;2. School of Computer Science and Engineering, Beihang University, Beijing 100191, PR China;3. School of Reliability and Systems Engineering, Beihang University, Beijing 100191, PR China;1. Department of Física y Matemáticas, Escuela Politécnica Superior de la Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, Spain;2. Department of Teoría de la Señal y Comunicaciones, Escuela Politécnica Superior de la Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, Spain;1. School of Information Science and Engineering, Yanshan University, QinHuangDao 066004, Hebei Province, PR China;2. Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Yanshan University, Qinhuangdao 066004, Hebei Province, PR China;3. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA;1. Department of Power Engineering, University of Split, Rudera Boskovica 32, 21000 Split, Croatia;2. Department of Electronics, University of Split, Rudera Boskovica 32, 21000 Split, Croatia;3. Department of Electrical Engineering and Information Technology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany;1. Chukyo University, Yagotohonmachi 101-2, Nagoya Showa-ku, Aichi 466-8666, Japan;2. Toyama Prefectural University, Kurokawa 5180, Imizu, Toyama 93939-0398, Japan;3. Hosei University, Kajinocho 3-7-2, Koganei, Tokyo 184-8584, Japan;1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, PR China;2. Institute of Vehicles and Energy, Yanshan University, Qinhuangdao, Hebei 066004, PR China |
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| Abstract: | The empirical mode decomposition (EMD) has recently emerged as an efficient tool to adaptively decompose non-stationary signals for nonlinear systems, which has a wide range of applications such as automatic control, mechanical engineering and medicine and biology. A noise-assisted variant of EMD named ensemble empirical mode decomposition (EEMD) have been proposed to alleviate the mode mixing phenomenon. In this paper, we proposed an improved EEMD method, namely cardinal spline interpolation based EEMD (C-EEMD), by optimizing the sifting procedure. Specifically, we employ the adjustable cubic trigonometric cardinal spline interpolation (CTCSI) to accurately represent free curves, other than the original one used in the traditional EEMD. The new interpolation approach can be used to build the mean curve in a more precise way. By virtue of CTCSI, we can therefore obtain the mean value curve from midpoints of the local maxima and minima by just one interpolation operations, which saves almost half the computational cost. Extensive experimental results on synthetic data and real EMI signals clearly demonstrate the superiority of the proposed method, compared to the state-of-the-arts. |
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| Keywords: | Ensemble empirical mode decomposition Electromagnetic interference signals Electromagnetic compatibility |
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