Multivariate Nonstationary Oscillation Simulation of Climate Indices with Empirical Mode Decomposition
نویسندگان
چکیده
منابع مشابه
Multivariate Empirical Mode Decomposition for Quantifying Multivariate Phase Synchronization
Quantifying the phase synchrony between signals is important in many different applications, including the study of the chaotic oscillators in physics and the modeling of the joint dynamics between channels of brain activity recorded by electroencephalogram (EEG). Current measures of phase synchrony rely on either the wavelet transform or the Hilbert transform of the signals and suffer from con...
متن کاملMultivariate empirical mode decomposition and application to multichannel filtering
Empirical Mode Decomposition (EMD) is an emerging topic in signal processing research, applied in various practical fields due in particular to its data-driven filter bank properties. In this paper, a novel EMD approach called X-EMD (eXtended-EMD) is proposed, which allows for a straightforward decomposition of monoand multivariate signals without any change in the core of the algorithm. Qualit...
متن کاملNoise-assisted multivariate empirical mode decomposition for multichannel EMG signals
BACKGROUND Ensemble Empirical Mode Decomposition (EEMD) has been popularised for single-channel Electromyography (EMG) signal processing as it can effectively extract the temporal information of the EMG time series. However, few papers examine the temporal and spatial characteristics across multiple muscle groups in relation to multichannel EMG signals. EXPERIMENT The experimental data was ob...
متن کاملEmpirical mode decomposition with missing values
This paper considers an improvement of empirical mode decomposition (EMD) in the presence of missing data. EMD has been widely used to decompose nonlinear and nonstationary signals into some components according to intrinsic frequency called intrinsic mode functions. However, the conventional EMD may not be efficient when missing values are present. This paper proposes a modified EMD procedure ...
متن کاملMultiband Prediction Model for Financial Time Series with Multivariate Empirical Mode Decomposition
This paper presents a subband approach to financial time series prediction. Multivariate empirical mode decomposition MEMD is employed here for multiband representation of multichannel financial time series together. Autoregressivemoving average ARMA model is used in prediction of individual subband of any time series data. Then all the predicted subband signals are summed up to obtain the over...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Water Resources Research
سال: 2019
ISSN: 0043-1397,1944-7973
DOI: 10.1029/2018wr023892