1. A method comprising: receiving a synchronously sampled output of a partial response channel, said output corrupted by noise; and processing, at the [i]th received output of the partial response channel, by: using (a) a window of N most recent noisy outputs of the partial response channel, (b) all distinct sequences of N most recent noiseless outputs possible at the output of the partial response channel, (c) the prior probability of each distinct sequence of N most recent noiseless outputs, and (d) an index j of a noiseless sampled output in the window to be estimated, determining a set of quantities, each said quantity related to the conditional probability of a noiseless sequence given the window of noisy channel outputs; determining a metric, for each possible noiseless sampled output level in the [j]th sample in the window, by adding a subset of the quantities; comparing the determined metrics to find the noiseless sampled output level with largest conditional probability; and generating the noiseless sampled output level with largest conditional probability as an estimate of the [i−N+j]th noiseless output of the partial response channel.