Improved Independent Component Analysis Based on Ant Colony Algorithm
Yuliang Xu · Video Engineering · 2011
The FastICA algorithm has the defect in relying on the selection of nonlinear functions.In order to improve the reliability of the separation results,an improved independent component analysis algorithm based on ant colony algorithm is introduced.Such algorithm has no special requirements of nonlinear function,takes the approximate expression of negative entropy as the objective function,and can be optimized by taking use of ant colony algorithm instead of Newton gradient method.The best separation matrix is found and then the independent components from the mixed signals are separated.Simulation result proves the improved independent component analysis algorithm is effective and better.