Title :
FastICA-EMD algorithm for analysis of the mixed signals in noise
Author :
Tianliang, Peng ; Qingtao, Chen ; Zengli, Liu ; Dongdong, Xu
Author_Institution :
Fac. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
Abstract :
Empirical mode decomposition (EMD) is an effective signal analysis method, which can decompose the original signal into several intrinsic mode functions(IMFs). In this paper a new signal analysis method of FastICA-EMD is introduced. The method is illustrated on simulated and real data, and the results are compared to traditional EMD method. The study is limited to signals that were corrupted by additive white Gaussian noise and is conducted on the basis of extended numerical experiments.
Keywords :
AWGN; independent component analysis; signal processing; additive white Gaussian noise; empirical mode decomposition; fast ICA-EMD algorithm; fixed-piont independent component analysis; intrinsic mode functions; mixed signal analysis method; Algorithm design and analysis; Approximation methods; Automation; Educational institutions; Entropy; Gaussian noise; Independent component analysis; Empirical mode decomposition(EMD); Fixed-piont independent component analysis(FastICA); Signal analysis;
Conference_Titel :
Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4577-0893-0
DOI :
10.1109/ICSPCC.2011.6061593
