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Error propagation nets have been shown to be able to learn a variety of tasks in which a static input pattern is mapped outo a static output pattern. This paper presents a generalisation of these nets to deal with time varying, or dynamic patterns, and three possible architectures are explored. As an example, dynamic nets are applied to tbe problem of(More)
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