Equivariant algorithms for selective transmission

We consider the problem of selective transmission-the dual of the blind source separation task-in which a set of independent source signals are adaptively premixed prior to a non-dispersive physical mixing process so that each source can be independently monitored in the far field. We derive a stochastic gradient algorithm for iteratively-estimating the premixing matrix in the selective transmission problem, and through a simple modification, we obtain a second algorithm whose performance is equivariant with respect to the channel´s mixing characteristics. We also describe an approximate version of the equivariant algorithm and other implementation issues. Simulations indicate the useful behavior of the premixing algorithms for selective transmission