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Artificial Neural Networks: Enhanced Back Propagation in Character Recognition
Abstract
The initial weights in Back Propagation has a strong influence in the learning speed and the quality of the solution obtained after convergence. The main objective of the research is to improve the performance of BP through three concepts: First, propagating the error back to the weights without squaring; second, limiting the initial randomly-generated weights to a certain range; and third, starting the matrix of weights with an ID matrix.
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