Underdetermined Blind Source Separation for Sparse Signals Based on the Law of Large Numbers and Minimum Intersection Angle Rule
| Autor: | Pengfei Xu, Yinjie Jia, Zhijian Wang, Mingxin Jiang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Underdetermined system business.industry Computer science Applied Mathematics 02 engineering and technology Blind signal separation Transplantation 020901 industrial engineering & automation Intersection Law of large numbers Simple (abstract algebra) Signal Processing Shortest path problem business Algorithm Digital signal processing |
| Zdroj: | Circuits, Systems, and Signal Processing. 39:2442-2458 |
| ISSN: | 1531-5878 0278-081X |
| Popis: | Underdetermined blind source separation (UBSS) is an important issue for sparse signals, and a novel two-step approach for UBSS based on the law of large numbers and minimum intersection angle rule (LM method) is presented. In the first step, an estimation of the mixed matrix is obtained by using the law of large numbers, and the number of source signals is displayed graphically. In the second step, a method of estimating the source signals by the minimum intersection angle rule is proposed. The significance of this step is that the minimum intersection rule is better than the shortest path method, and the decomposition components can be found optimally by the former. The simulation results illustrate the effectiveness of the LM method. It has a simple principle, has good transplantation capability and may be widely applied in various fields of digital signal processing. |
| Databáze: | OpenAIRE |
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