Source Number Estimation and Effective Channel Order Determination Based on Higher-Order Tensors
| Autor: | Kan Xie, Yuan Xie, Shengli Xie |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Series (mathematics) Underdetermined system Channel (digital image) Computer science Applied Mathematics 02 engineering and technology Mixture model Blind signal separation Matrix (mathematics) 020901 industrial engineering & automation Signal Processing Tensor Algorithm Eigenvalues and eigenvectors |
| Zdroj: | Circuits, Systems, and Signal Processing. 38:5393-5408 |
| ISSN: | 1531-5878 0278-081X |
| DOI: | 10.1007/s00034-019-01106-0 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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