Abstract
The authors present an ML (maximum-likelihood) deconvolution algorithm for estimating non-white B-G (Bernoulli-Gaussian) signals μ(k), which were distorted by a linear time-invariant system v(k). The measured spectrum of μ(k) such as that obtained from sonic logs is taken into account. Simulation results are presented to demonstrate the good performance of the proposed ML blind deconvolution algorithm for non-white B-G signals.