Computer Engineering and Applications ›› 2014, Vol. 50 ›› Issue (6): 210-212.

### Research on improved FastICA algorithms

ZHANG Jie, LIU Hui, OU Lunwei

1. Institute of Physics and Information Science, Hunan Normal University, Changsha 410081, China
• Online:2014-03-15 Published:2015-05-12

### 改进的FastICA算法研究

1. 湖南师范大学 物理与信息科学学院，长沙 410081

Abstract: Independent Component Analysis（ICA） is the blind source separation algorithm which is one of the most commonly used methods. And the Fast Independent Component Analysis（FastICA） with its convergence speed is widely used. But FastICA is sensitive to the choice of initial value, and in the use of Newton iterative method, each iteration step is needed to calculate a function value and a derivative value. When the function is more complex, computing its derivatives is often not convenient. This paper uses the single point string section method to iterate. Combining the steepest descent method with the single point string section method, while ensuring the separation effect, it makes FastICA iterative times reduce. At the same time it makes the calculation type more concise, and reduces the sensitivity to the initial value.