Reproducing Infinite Boolean Sequences: an Application of Hidden Markov Models to Connectionist Learning
نویسنده
چکیده
Given the first few terms of an infinite sequence of 0’s and 1’s, build a network that reproduces the rest of the sequence. To accomodate this learning task, a framework is developed for learning, general enough to include learning of finite-length input, finite-length output as well. The similarities between the finite and infinite learning tasks are considered and parallels are drawn to the speech recognition problem. Several properties of infinite length learning are obtained, using Hidden Markov Model theory.
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