The Sparse Blume\tire Emery\tire Griffiths Model of Associative Memories
2018, v.24, Issue 5, 779-810
We analyze the Blume\tire Emery\tire Griffiths (BEG) associative memory with sparse patterns and at zero temperature.
We give bounds on its storage capacity provided that we want the stored patterns to be
fixed points of the retrieval dynamics. We compare our results to that of other models of sparse neural networks and
show that the BEG model has a superior performance compared to them.
Keywords: Associative memory, storage capacity, sparse data, artificial intelligence, machine learning, exponential inequalities, negative association