Convergence analysis of sign-sign LMS algorithm for adaptive filters with correlated Gaussian data

This paper presents a statistical behavior analysis of a sign-sign least mean square algorithm, which is obtained by clipping both the reference input signal and the estimation error, for adaptive filters with correlated Gaussian data. The study focuses on the derivation of expressions for the first and second moment behavior of the filter coefficient vector and analysis of the filter mean square error. The previous analysis of this type for the sign-sign algorithm is based on the assumption that the input sequence to the adaptive filter is independent, identically distributed Gaussian, but this restriction is removed in our analysis. Theoretical expressions derived are verified numerically through computer simulations for an example of system identification.