Enhancing the super exponential method of blind equalisation with the fast RLS Kalman algorithm

A method for efficiently implementing super exponential (SE) blind equalisation is proposed. The method, based on fast Kalman filtering theory, is recursive in order and in time, and leads to a significant reduction in the number of arithmetic operations. Using the order update by partitioning the covariance matrix of the first hundred data in a specific form, a fast initialisation is implemented. The resulting algorithm achieves the same theoretical fast convergence characteristics as the original SE algorithm but with a significant reduction in arithmetic operations