Sliding Window Empirical Mode Decomposition -its performance and quality
نویسنده
چکیده
Correspondence: [email protected] Nalecz Institute of Biocybernetics and Biomedical Engineering PAS, Warsaw, Poland Abstract Background: In analysis of nonstationary nonlinear signals the classical notion of frequency is meaningless. Instead one may use Instantaneous Frequency (IF) that can be interpreted as the frequency of a sine wave which locally fits the signal. IF is meaningful for monocomponent nonstationary signals and may be calculated by Hilbert transform (HT).
منابع مشابه
EPJ Nonlinear Biomedical Physics
Background The chess game is a good example of cognitive task which needs a lot of training and experience. The aim of this work is to compare applicability of two nonlinear methods Higuchi Fractal Dimension and Empirical Mode Decomposition in analysis of EEG data recorded during chess match. We analyzed data of three master chess players registered during their matches with computer program. M...
متن کاملThe Time-Dependent Intrinsic Correlation Based on the Empirical Mode Decomposition
A Time-Dependent Intrinsic Correlation (TDIC) method is introduced. This new approach includes both autoand cross-correlation analysis designed especially to analyze, capture and track the local correlations between nonlinear and nonstationary time series pairs. The approach is based on Empirical Mode Decomposition (EMD) to decompose the nonlinear and nonstationary data into their intrinsic mod...
متن کاملEmpirical Mode Decomposition based Adaptive Filtering for Orthogonal Frequency Division Multiplexing Channel Estimation
This paper presents an empirical mode decomposition (EMD) based adaptive filter (AF) for channel estimation in OFDM system. In this method, length of channel impulse response (CIR) is first approximated using Akaike information criterion (AIC). Then, CIR is estimated using adaptive filter with EMD decomposed IMF of the received OFDM symbol. The correlation and kurtosis measures are used to sel...
متن کاملCombination of Empirical Mode Decomposition Components of HRV Signals for Discriminating Emotional States
Introduction Automatic human emotion recognition is one of the most interesting topics in the field of affective computing. However, development of a reliable approach with a reasonable recognition rate is a challenging task. The main objective of the present study was to propose a robust method for discrimination of emotional responses thorough examination of heart rate variability (HRV). In t...
متن کاملBlind Voice Separation Based on Empirical Mode Decomposition and Grey Wolf Optimizer Algorithm
Blind voice separation refers to retrieve a set of independent sources combined by an unknown destructive system. The proposed separation procedure is based on processing of the observed sources without having any information about the combinational model or statistics of the source signals. Also, the number of combined sources is usually predefined and it is difficult to estimate based on the ...
متن کامل