A two-stage based approach for extracting periodic signals

Authors:
Zhi-Lin Zhang;Liqing Zhang
Affiliations:
Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China;Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China
Venue:
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Year:
2006

Citing 9
Cited 4

A fast fixed-point algorithm for independent component analysis

Neural Computation
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications

Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Extraction of Specific Signals with Temporal Structure

Neural Computation
Letters: Robust extraction of specific signals with temporal structure

Neurocomputing
Letters: Extraction of temporally correlated sources with its application to non-invasive fetal electrocardiogram extraction

Neurocomputing
Sequential blind source separation based exclusively on second-order statistics developed for a class of periodic signals

IEEE Transactions on Signal Processing
Exploring fMRI data for periodic signal components

Artificial Intelligence in Medicine
From blind signal extraction to blind instantaneous signal separation: criteria, algorithms, and stability

IEEE Transactions on Neural Networks
Approach and applications of constrained ICA

IEEE Transactions on Neural Networks

Morphologically constrained ICA for extracting weak temporally correlated signals

Neurocomputing
Two-Stage temporally correlated source extraction algorithm with its application in extraction of event-related potentials

ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
A flexible algorithm for extracting periodic signals

ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Harmonic retrieval by period blind source extraction method: Model and algorithm

Digital Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In many applications, such as biomedical engineering, it is often required to obtain specific periodic source signals. In this paper, we propose a two-stage based approach for extracting periodic signals. At the first stage, the autocorrelation property of the desired source signal is exploited to roughly extract the desired source signal. At the second stage, the extracted signal is further processed as cleanly as possible, based on the higher-order statistics. Simulations on artificially generated data and real-world ECG data have showed its better performance, compared with many existing extraction algorithms.