New alternative Class 3 adaptive filter algorithms

New alternative Class 3 adaptive filter algorithms are presented. Class 3 algorithms require no a priori information knowledge about the signal and noise that are being processed. Their performance depends upon the kind of smoothing used and on the signals and noises being processed by the filter. The previously published Class 3 filter algorithms require that the filter input be stationary and that the noise spectrum have zero mean and be uncorrelated to the signal. For the new Class 3 adaptive filter algorithms, the only additional assumption for the noise is that its spectrum be white. Simulations using EKG signals demonstrate much better performance using the new Class 3 algorithms over the standard Class 3 algorithms.