KAGE: a new fast RLS algorithm

A new fast recursive least squares (RLS) algorithm is introduced. By making use of RLS interpolation as well prediction, the algorithm generates the transversal filter weights without suffering the poor numerical attributes of the FTF algorithm. The Kalman gain vector is generated at each time step in terms of interpolation residuals. The interpolation residuals are calculated in an order recursive manner. For an Nth order problem the procedure requires O(NlogN) operations. This is achieved via a divide and conquer approach. Computer simulations suggest the new algorithm is numerically robust, running successfully for many millions of iterations