Recursive Least-Squares Lattice Adaptive Algorithm Suitable for Fixed-Point Implementation

This paper proposes a version of recursive least-squares lattice (RLSL) adaptive algorithm suitable for fixed-point implementation. It is based on a modified form of the cost function in order to obtain an asymptotically unbiased estimator of the mean-square error, reducing significantly the dynamic range of the algorithm's parameters. Moreover, in order to achieve an enhanced numerical accuracy an error-feedback mechanism is employed. These improvements lead to facilities for fixed-point implementations.