Analysis of a sign algorithm with delayed data

An adaptive filter whose weights are adapted using a sign algorithm with a delayed error signal is analyzed. For stationary environments it is proved that the excess average absolute estimation error is bounded for all values of the error signal delay and the algorithm step size. For the nonstationary case when the optimal filter weights are time varying, the optimum step size which minimizes the excess average absolute error is derived. It is shown that the optimum step size does not depend on the additive noise power. The analytical results are supported by computer simulations