PATTERN RECOGNITION ABILITIES OF RECURRENT NEURAL NETWORKS
The artificial neural networks are simulating the human brain. Could artificial neural networks memorize as the human brain? The paper presents the structures, the learning rules and the stability of the Hopfield, Bidirectional Associative Memory (BAM), two main recurrent neural networks. We also perform the experiments on their memory abilities, ability of fault isolation for several of failure bits. An example of pattern recognition of image faces and corresponding their labels are also represented.
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