Fourth International Conference on Computer and Information Technology (CIT'04)
Signal Extensions in Independent Component Analysis and Its Application for Real-Time Processing
Wuhan, China
September 14-September 16
ISBN: 0-7695-2216-5
In this paper, we investigate some issues related to real-time processing for independent component analysis (ICA), based on gradient learning with simultaneous perturbation stochastic approximation (SPSA). Real-time ICA processing is especially necessary for an application in dynamic mixing environment, since a batch type of ICA processing can work well only in a static or stationary mixing environment. Although there are many choices for an ICA object function to which SPSA can be applied, in this paper, we choose a diagonality of the non-linear correlation matrix as our object function. Theories and implementations of the algorithm are described. Results of computer simulation are also presented to demonstrate the effectiveness.
Citation:
Shuxue Ding, Jie Huang, Daming Wei, Sadao Omata, "Signal Extensions in Independent Component Analysis and Its Application for Real-Time Processing," cit, pp.839-844, Fourth International Conference on Computer and Information Technology (CIT'04), 2004