Coefficient wordlength limitation in FLS adaptive filters

A stability condition analysis is performed for weighted Least Squares Algorithms. It is shown that the introduction of a constant in the prediction error energy updating recursion can make the algorithm stable. Coefficient wordlength estimations can then be derived from those available for Least Mean Squares Algorithms. The results given are useful in designing adaptive filters based on least squares techniques in their simplest forms.