Neural network for the exact RLS adaptive algorithm

摘要

This paper proposes a neural network approach to the implementation of the exact recursive least-squares (RLS) algorithm. We show that the proposed neural network is guaranteed to be stable and to provide the results arbitrarily close to the accurate optimal solution of the RLS algorithm within an elapsed time of only a few characteristic time constants of the network. The parameters of the network (such as interconnections strengths and bias currents) can be obtained from the available data with a few computations, which are much fewer than the computations required in the exact RLS algorithm; as a result, this proposed scheme is very suitable for real time applications of the exact RLS algorithm.