Maximizing theoretical and practical storage capacity in single-layer feedforward neural networks
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Artificial neural networks are limited in the number of patterns that they can store and accurately recall, with capacity constraints arising from factors such as network size, architectural structure, pattern sparsity, and pattern dissimilarity. Exceeding the... ...
