ICA Algorithm Based on Subspace Approach

Generally, the blind separation algorithms based on the subspace approach are very slow. In addition, they need a considerable computation e ort and time due to the estimation and the minimization of huge matrices. Previously, we proposed an adaptive subspace criterion to solve the blind separation problem [1]. The criterion has been minimized adaptively using a conjugate gradient algorithm [2]. Unfortunately, the convergence of that algorithm needed more than one hour of computational time using an ultra sparc 30 and "C" code program. In this paper, we improve that criterion by proposing a new subspace adaptive algorithm. The new algorithm deals with stationary signals. The experimental results show that the convergence of the new algorithm is relatively fast due to the estimation by bloc of the different matrices and the minimization of the cost function using a generalized conjugate gradient method.