An Introduction to Learning Structured Information

Connectionist models for sequence processing are based on the same recursive state updating scheme that characterizes the state space representation used in system theory to describe nonlinear dynamical systems. In this paper, we introduce a graphical computational framework for learning data structures, but little emphasis is given to specific models and learning algorithms.

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