P.O. Pavlovichev – Post-graduate Student, P.G. Demidov Yaroslavl State University E-mail: assault74@rambler.ru
A.L. Priorov – Dr.Sc. (Eng.), Associate Professor, P.G. Demidov Yaroslavl State University
E-mail: andcat@yandex.ru
A.I. Topnikov – Ph.D. (Eng.), Associate Professor, P.G. Demidov Yaroslavl State University E-mail: topartgroup@gmail.com
The paper is devoted to an empirical mode decomposition – it is a method that allows to analyze non-stationary signals. Initial mathematical formula of the difference is demonstrated that proposed by authors of the decomposition method, and we show that its practical application can lead to criterion incorrect operation that embarrasses the mode sifting. We propose the transformed mathematical formula of the quadratic difference that provides the criterion proper operation, and we demonstrate modeling results for a test and speech signal.
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- Wenyu Zhang, Yaning Li, Jianzhou Wang, Zhangli Dang Forecasting wind speed using empirical mode decomposition and Elman neural network // Applied Soft Computing. 2014. V. 23. P. 452–459.
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- Nader Fnaiech, Lotfi Saidi, Brigitte Chebel-Morello, Farhat Fnaiech Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals // Applied Acoustics. 2015. V. 89. P. 16–27.
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- Anmin Gonga, Binghe Wang, Yi Qu, YaoRui Zheng Modulation type recognition of OFDM signals based on EMD // Applied Mechanics and Materials. 2015. V. 721. P. 670–673.
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