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

fYear

2011

fDate

14-16 Sept. 2011

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4577-0893-0

Type

conf

DOI

10.1109/ICSPCC.2011.6061593

Filename

6061593