Error bound method and its application to the LMS algorithm

A method to determine a bound on the error performance of an adaptive filter due to roundoff effects is described. The method converts the analysis of a recursive algorithm into two much simpler sub-problems: convergence and momentary error. To apply the method, the input data has to be bounded. By classifying convergence into different categories according to their rates, it is observed that adaptive filtering algorithms that belong to a particular class share similar behavior due to roundoff error or other perturbation effects. The merit of the method is its simplicity and general applicability. Based on this method, a sufficient condition for the numerical stability of an adaptive filter is derived. Application of the method to the least mean square (LMS) algorithm is described. The analysis may also be generalized to include other perturbation effects.<>