Model
Digital Document
Publisher
Florida Atlantic University
Description
A novel neural network, trained with the Alopex algorithm to recognize handprinted characters, was developed in this research. It was constructed by an encoded fully connected multi-layer perceptron (EFCMP). It consists of one input layer, one intermediate layer, and one encoded output layer. The Alopex algorithm is used to supervise the training of the EFCMP. Alopex is a stochastic algorithm used to solve optimization problems. The Alopex algorithm has been shown to accelerate the rate of convergence in the training procedure. Software simulation programs were developed for training, testing and analyzing the performance of this EFCMP architecture. Several neural networks with different structures were developed and compared. Optimization of the Alopex algorithm was explored through simulations of the EFCMP training procedure with the use of different parametric values for Alopex.
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