期刊论文、会议论文

Pang, Lihui

英文

PROCEEDINGS OF 2016 IEEE 13TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP 2016)

2164-5221

2017

1440-1445

13th IEEE International Conference on Signal Processing (ICSP)

International Conference on Signal Processing

NOV 06-10, 2016

Chengdu, PEOPLES R CHINA

[Deng, Xianrong] MStar Semicond Inc, Hardware Designing Dept, Shenzhen, Peoples R China.^[Pang, Lihui;Wang, Xinlin] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.^[Jiang, Kaili] Univ Elect Sci & Technol China, Sch Elect Engineer, Chengdu, Sichuan, Peoples R China.

IEEE, Inst Engn & Technol, Union Radio Sci Int, Chinese Inst Elect, Beijing Jiaotong Univ, Int Conf Signal Proc, IEEE Beijing Sect, IET Beijing Local Network, Natl Nat Sci Fdn China, CIE Signal Proc Soc, IEEE Signal Proc Soc Beijing Chapter, IEEE Comp Soc Beijing Chapter, Japan China Sci & Technol Exchange Assoc, Shenzhen Univ, Intelligent Informat Inst, CIC Commun & Signal Proc Soc, Univ Minist Educ China, Program Innovat Res Team

Baozong, Y Qiuqi, R Yao, Z Gaoyun AN

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

978-1-5090-1345-6

10.1109/ICSP.2016.7878064

Scientific Research Foundation of University of South China [2015XQD05]; research project of Hunan Provincical Department of Education [r2016SJY57]

本校为通讯机构

This paper presents a new methodology for single-channel blind signal separation (SCBSS) of time-frequency overlapped signals in electromagnetic surveillance domain. This method combines the complete ensemble empirical mode decomposition (CEEMD) with fast independent component analysis (FastICA). Firstly, the single-channel recording is decomposed into a set of intrinsic mode function (IMF) components by the method CEEMD with adaptive noise, for the residue and the number of shifting iterations of CEEMD are smaller than that of other empirical mode decomposition approach. The IMF components be...