On the information rate of binary-input channels with memory

The entropy rate of a finite-state hidden Markov model can be estimated by forward sum-product trellis processing (i.e., the forward recursion of the Baum-Welch/BCJR algorithm) of simulated model output data. This can be used to compute information rates of binary-input AWGN channels with memory.