The neural network training model can be considered as a processor that acquires and stores experiential knowledge through a machine learning process. In order to retain the knowledge, synaptic weights that resemble interneuron connections are used. The training process of a learning algorithm involves the modification of the synaptic weights of the model in order to obtain a desired objective.