Dynamic Convergence of LMS Algorithm Using New Step Size

LMS Algorithm already has a standard step-size, mu. This paper still optimizes the existing step-size, while it is under processing. It simply introduces a dynamically varying parameter at the denominator of the step-size so that the convergence rate of the system will drastically improve. Mean time this empirical result shows that the unstable problem of the LMS algorithm is also minimized to the large extends.