Complexity reduction in fast RLS transversal adaptive filters with application to acoustic echo cancellation

Fast recursive least squares (RLS) adaptive filters are still too complex for many applications. The authors discuss the fast Newton transversal filters (FNTFs), a new family of fast RLS filters based on prediction order reduction, which can have complexity close to that of LMS. A simple derivation of the FNTF is presented, and implementation, initialization, and stabilization issues, which are taken from fast RLS practice, are considered. When evaluating complexity, it is shown that FNTF filters with lengths appropriate for acoustic echo cancellation can be implemented on one standard floating point digital signal processor (DSP). Experimental performances on speechlike and real signals are very close to those of the standard fast RLS