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O, φ=. Supervised learning consists of finding particular mapping φ that not only approximates input patterns correctly but has the property of generalization for test patterns as well. The learning process is performed with fixed topology and activation functions only through synoptic weights adjustment. In other words for a given set of input images ()(){} m m