Gradient-based adaptive algorithm with an optimum vector of convergence factors

An alternative perspective of adaptive filtering by way of optimization theory is presented. We derive an optimum vector of convergence factors for a general-structure adaptive filter and the gradient algorithm. It is proved that the optimum vector of convergence factors produces a faster convergence compared with the optimum but single convergence factor.