A Euclidean direction based algorithm for blind source separation using a natural gradient

The paper develops an extension of the adaptive RLS-type algorithm proposed by X.-L. Zhu and X.-D. Zhang (see IEEE Sig. Process. Lett., vol.9, no.12, p.432-5, 2002). Their work uses the matrix inversion lemma to solve iteratively the equation obtained from the natural gradient of the nonlinear principle component analysis problem. We reduce the complexity of the solution by applying the Euclidean direction search concept in place of the matrix inversion lemma. The simulations performed show that the convergence rate is comparable, albeit slower, but with reduced complexity per iteration.