A 2ND-ORDER RECURSIVE ALGORITHM WITH APPLICATIONS TO ADAPTIVE FILTERING AND SUBSPACE TRACKING

A second-order recursive algorithm for adaptive signal processing is p roposed, and a similar algorithm is derived for signal subspace tracki ng. It is shown that the algorithm encompasses both the RLS and the LM S algorithms as special cases. The computational complexity is the sam e as for the RLS algorithm, but some extra memory storage is required. The associated ordinary differential equation (ODE) for the autoregre ssive exogenous (ARX) case algorithm is proven to be globally exponent ially stable. Furthermore, it is demonstrated that the proposed algori thm has a higher ability to track time-varying signals than has the RL S algorithm. The proposed algorithm especially handles those situation s well where there is a simultaneous system change and decrease of sig nal power.