Paper Info
Title
Source Number Estimation and Effective Channel Order Determination Based on Higher-Order Tensors
Abstract
Source number estimation is an essential task in underdetermined convolutive blind source separation, and effective channel order determination is also a challenging issue. For solving the two problems, the classical methods are based on information theoretic criteria. However, these are prone to the underestimation and overestimation of the number of sources in the underdetermined case. To compensate for this shortcoming, in this paper we propose two algorithms based on higher-order tensors. First, an improved algorithm is presented to estimate the number of sources. By transforming the tensor into a matrix, the eigenvalues of the resultant matrices are used to estimate the number of sources. Additionally, we employ higher-order tensors to detect the effective channel order and confirm the relationship between the number of sources and the effective channel order in the convolutive mixture model. Finally, a series of simulation experiments demonstrate that the proposed algorithms have an advantage over the conventional methods.
Year
DOI
Venue
2019
10.1007/s00034-019-01106-0
Circuits, Systems, and Signal Processing
Keywords
Field
DocType
Source number estimation, Effective channel order determination, Information theoretic criteria, Higher-order tensors
Mathematical optimization,Tensor,Underdetermined system,Matrix (mathematics),Algorithm,Communication channel,Blind signal separation,Mixture model,Mathematics,Eigenvalues and eigenvectors
Journal
Volume
Issue
ISSN
38
11
0278-081X
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Yuan Xie140727.48
Kan Xie235128.49
Shengli Xie32530161.51