Using Tags to Improve Diversity of Sparse Associative Memories
Résumé
Associative memories, a classical model for brain long-term memory, face interferences between old and new memories. Usually, the only remedy is to enlarge the network so as to retain more memories without collisions: this is the network's size-diversity trade-off. We propose a novel way of representing data in these networks to provide another mean to extend diversity without resizing the network. We show from our analysis and simulations that this method is a viable alternative, which can perfectly fit cases where network's size is constrained such as neuromorphic FPGA boards implementing associative memories.