FFT-based RLS in signal processing

An algorithm for fast adaptive filtering is proposed. The algorithm applies a FFT (fast Fourier transform)-based iterative method and uses sliding data windows involving block updating and downdating computations. The method is stable and robust, and computes the tap weight filter vector in O(L log N) operations, where the sliding window Toeplitz data matrix X is L-by-N. The complexity thus generally lies between those of the family of unstable but fast, O(N), methods and the stable but slow O(N/sup 2/) Cholesky factor updating methods.