Underdetermined Independent Component Analysis Based on First- and Second-Order Statistics
| Autor: | Changliang Deng, Yimin Wei, Yuehong Shen, Qiao Su |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Beamforming
0209 industrial biotechnology Underdetermined system Computer science Applied Mathematics Reliability (computer networking) 02 engineering and technology Conditional expectation Independent component analysis Class (biology) Matrix (mathematics) 020901 industrial engineering & automation Mixing (mathematics) Signal Processing Algorithm |
| Zdroj: | Circuits, Systems, and Signal Processing. 38:3107-3132 |
| ISSN: | 1531-5878 0278-081X |
| Popis: | This paper proposes a class of new algorithms based on first- and second-order statistics for independent source extraction of circular signals in underdetermined complex-valued mixture. The complex-valued mixing matrix is estimated by two extremely cost-effective novel methods based on the conditional mean of the mixtures which require some prior knowledge of the positive support of the real and/or imaginary parts of the sources. And the sources are recovered by combining the conventional minimum mean-squared error-based beamforming approach with the acquired prior knowledge. Based on how much prior knowledge is got, we propose several new algorithms. The complexity analysis about the proposed algorithms suggests that the algorithms which employ more prior knowledge have higher complexity, but their computational cost is significantly low. Two examples are provided for showing the possible applications of these proposed algorithms. Simulation results validate the effectiveness and reliability of all presented methods. |
| Databáze: | OpenAIRE |
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