Adaptive line enhancement using a random AR model

The objective of this report is to investigate the possibility of using random autoregressive (AR) models in signal processing problems. The advantage of this approach is that they may reflect more accurately the uncertainity in the stochastic process that generates the received signal. The method is applied to adaptive line enhancement where it is shown through Monte Carlo simulations, that it yields better results than the conventional deterministic AR models under the same conditions.