Paper Info
Title
Investigation of Short-Term Changes in Visual Evoked Potentials With Windowed Adaptive Chirplet Transform
Abstract
We propose a new application of the adaptive chirplet transform that involves partitioning signals into non-overlapping sequential segments. From these segments, the local time-frequency structures of the signal are estimated by using a four-parameter chirplet decomposition. Entitled the windowed adaptive chirplet transform (windowed ACT), this approach is applied to the analysis of visual evoked potentials (VEPs). It can provide a unified and compact representation of VEPs from the transient buildup to the steady-state portion with less computational cost than its non-windowed counterpart. This paper also details a method to select the optimal window length for signal segmentation. This approach will be useful for long-term signal monitoring as well as for signal feature extraction and data compression.
Year
DOI
Venue
2008
10.1109/TBME.2008.918439
Biomedical Engineering, IEEE Transactions
Keywords
Field
DocType
bioelectric potentials,medical signal processing,neurophysiology,data compression,four-parameter chirplet decomposition,local time-frequency structures,long-term signal monitoring,nonoverlapping sequential segments,optimal window length,signal feature extraction,signal segmentation,surface electrical potentials,visual evoked potentials,windowed adaptive chirplet transform,Chirplet transform,optimal window length,short-term changes,time-frequency analysis,visual evoked potentials
Computer vision,Neurophysiology,Segmentation,Computer science,Chirplet transform,Feature extraction,Electronic engineering,Artificial intelligence,Time–frequency analysis,Chirp,Data compression,Wavelet transform
Journal
Volume
Issue
ISSN
55
4
0018-9294
Citations 
PageRank 
References 
4
0.42
4
Authors
2
Name
Order
Citations
PageRank
Cui, J.140.42
Willy Wong2283.71