A Systolic Array for Recursive Least Squares Computations - Part II : Mapping directionally weighted RLS on an SVD updating array

In an earlier paper, a systolic algorithm/array was derived for recursive least squares (RLS) estimation, which achieves an O(n0) throughput rate with O(n2) parallelism. The resulting array is specifically tuned towards the RLS problem. Here, a different route is taken, by trying to implement the RLS problem on a systolic array, which is also useful for several other applications, such as, e.g., SVD updating and Kalman filtering. This is important in view of possible hardware implementation. An additional advantage is that, unlike with the earlier array, it is now possible to incorporate alternative data weighting strategies such as directional weighting, without sacrificing speed.