TY - JOUR
T1 - A new approach to sparse decomposition of nonstationary signals with multiple scale structures using self-consistent nonlinear waves
AU - Young, Hsu Wen Vincent
AU - Hsu, Ke Hsin
AU - Pham, Van Truong
AU - Tran, Thi Thao
AU - Lo, Men Tzung
N1 - Publisher Copyright:
© 2017
PY - 2017/9/1
Y1 - 2017/9/1
N2 - A new method for signal decomposition is proposed and tested. Based on self-consistent nonlinear wave equations with self-sustaining physical mechanisms in mind, the new method is adaptive and particularly effective for dealing with synthetic signals consisting of components of multiple time scales. By formulating the method into an optimization problem and developing the corresponding algorithm and tool, we have proved its usefulness not only for analyzing simulated signals, but, more importantly, also for real clinical data.
AB - A new method for signal decomposition is proposed and tested. Based on self-consistent nonlinear wave equations with self-sustaining physical mechanisms in mind, the new method is adaptive and particularly effective for dealing with synthetic signals consisting of components of multiple time scales. By formulating the method into an optimization problem and developing the corresponding algorithm and tool, we have proved its usefulness not only for analyzing simulated signals, but, more importantly, also for real clinical data.
KW - Adaptive signal decomposition
KW - Optimization
KW - Self-consistent nonlinear equations
KW - Sparse representations
KW - Time–frequency analysis
UR - http://www.scopus.com/inward/record.url?scp=85017544204&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2017.04.009
DO - 10.1016/j.physa.2017.04.009
M3 - 期刊論文
AN - SCOPUS:85017544204
SN - 0378-4371
VL - 481
SP - 1
EP - 10
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -