This paper proposes a family of Recursive Least-Squares Lattice (RLSL) adaptive algorithms suitable for fixed-point implementation. These algorithms are 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 parameters. In order to achieve an enhanced numerical accuracy an error-feedback mechanism could be employed. These improvements lead to facilities for fixed-point implementations.

Keywords: Adaptive filters, RLSL adaptive algorithm, Fixed-point implementation.