On gradient adaptation with unit-norm constraints

{ In this correspondence, we describe gradient-based adaptive algorithms within parameter spaces that are speciied by jjwjj = 1, where jj jj is any vector norm. We provide several algorithm forms and relate them to true gradient procedures via their geometric structures. We also give algorithms that mitigate an inherent numerical instability for L 2-norm-constrained optimization tasks. Simulations showing the performance of the techniques for independent component analysis are provided. 0 Permission of the IEEE to publish this abstract separately is granted.