Post-ECC Modeling of Magnetic Recording Channels using Hidden Markov Models

In this paper, we present maximum-likelihood modeling of burst errors in magnetic recording channels using hidden Markov models (HMM). We derive low-complexity and memory efficient algorithms for computing the log-likelihood function for burst sequences, and use this algorithm to optimally determine the model parameters using smart search techniques. Finally, we illustrate a modeling example from real observed data collected from hard disks, and show how the model can be applied for evaluating decoder failure rates using Wolf´s method [5].