A technique to improve convergence speed of the LMS algorithm

This paper describes a technique for improving the convergence speed of the LMS algorithm. The main idea of the technique is to increase the number of updatings of the filter weights per unit time so that the convergence speed is accelerated according to the number of updatings. The validity of the technique is shown by considering the deriving process of the LMS algorithm from the steepest descent algorithm. We present the two example structures for implementing the technique in actual applications. Finally we show the results of computer simulations