The square-root Schur RLS adaptive filter

A square-root normalized Schur (1917,1986) RLS (recursive least squares) adaptive filter is presented which belongs to the newly developed class of Schur-type algorithms for adaptive filtering and parameter estimation in the serialized data case of RLS processing. Schur-type algorithms can outperform many of the well-known fast adaptive filtering algorithms due to their inherent ability to work with arbitrary recursive windowing of the data. Key features of the square-root Schur RLS adaptive filter are a fully pipelineable structure and excellent numerical properties. A systolic array of CORDIC processors for implementation of the square-root Schur RLS adaptive filter is presented, and its performance is illustrated with a typical example