On least square frequency-domain adaptive filters

This paper presents a least square approach to the Dentino et al. [1] frequency-domain adaptive filter by minimizing a frequencydomain error criterion. The constant that controls the LMS convergence behavior is replaced by an adaptive that every new iteration achieves this least squared error. The proposed approach can be extended and then applied to modify other frequency-domain adaptive algorithms. For example, a modified version of the unconstrained frequency domain adaptive algorithm proposed by Mansour and Gray in [2] is presented. The advantage of our modified unconstrained frequency-domain adaptive algorithm is that it has only one convergence parameter as compared to two in the original algorithm.