An Improved FastICA Algorithm Based on Modified-M Estimate Function
| Autor: | Jianfu Teng, Liuyi Yang, Xin Meng, Ping Xie |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Mathematical optimization
Fastica algorithm Iterative method Computer science Applied Mathematics Initialization 020206 networking & telecommunications 02 engineering and technology Independent component analysis Nonlinear system Rate of convergence Robustness (computer science) Signal Processing 0202 electrical engineering electronic engineering information engineering FastICA 020201 artificial intelligence & image processing Algorithm |
| Zdroj: | Circuits, Systems, and Signal Processing. 37:1134-1144 |
| ISSN: | 1531-5878 0278-081X |
| DOI: | 10.1007/s00034-017-0595-5 |
| Popis: | In order to improve the detection rate of ship information, fast independent component analysis (FastICA) algorithm is adopted to separate satellite-based automatic identification system (AIS) mixed signals. FastICA algorithm has the advantages of fast convergence rate and simple form. However, it is sensitive to the initialization of the separation matrix and the robust performance is poor. Aimed at the problem, an improved FastICA algorithm is proposed. This new algorithm is based on constant model of AIS signal and chooses Modified-M estimation function as nonlinear function so as to improve the robustness of algorithm. The improved algorithm also modifies Newton iterative algorithm. The experimental simulation results indicate that the proposed method reduces the iteration times and the accuracy has been improved. |
| Databáze: | OpenAIRE |
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