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Based on the concept of fuzzy sets defined by Zadeh, a class of fuzzy automata is formulated similar to Mealy's formulation of finite automata. A fuzzy automaton behaves in a deterministic fashion. However, it has many properties similar to that of stochastic automata. Its application as a model of learning systems is discussed. A nonsupervised learning scheme in automatic control and pattern recognition is proposed with computer simulation results presented. An advantage of employing fuzzy automaton as a learning model is its simplicity in design and computation.