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We study the classical problem of noisy constrained capacity in the case of the binary symmetric channel (BSC), namely, the capacity of a BSC whose input is a sequence from a constrained set. As stated by Fan , “... while calculation of the noise-free capacity of constrained sequences is well known, the computation of the capacity of a constraint in the presence of noise ... has been an unsolved problem in the half-century since Shannon's landmark paper.” We first express the constrained capacity of a binary symmetric channel with (d,k)-constrained input as a limit of the top Lyapunov exponents of certain matrix random processes. Then, we compute asymptotic approximations of the noisy constrained capacity for cases where the noise parameter ε is small. In particular, we show that when k ≤ 2d, the error term (excess of capacity beyond the noise-free capacity) is O(ε) , whereas it is O(εlogε) when k > 2d. In both cases, we compute the coefficient of the error term. In the course of establishing these findings, we also extend our previous results on the entropy of a hidden Markov process to higher-order finite memory processes. These conclusions are proved by a combination of analytic and combinatorial methods.