Tree-like hierarchical associative memory structures

In this letter we explore an alternative structural representation for Steinbuch-type binary associative memories. These networks offer very generous storage capacities (both asymptotic and finite) at the expense of sparse coding. However, the original retrieval prescription performs a complete search on a fully-connected network, whereas only a small fraction of units will eventually contain desired results due to the sparse coding requirement. Instead of modelling the network as a single layer of neurons we suggest a hierarchical organization where the information content of each memory is a successive approximation of one another. With such a structure it is possible to enhance retrieval performance using a progressively deepening procedure. To backup our intuition we provide collected experimental evidence alongside comments on eventual biological plausibility.

• Type: Journal
• Year: 2011
• Where: NN
• Authors: João Sacramento, Andreas Wichert
• Keywords: Binary Associative Memories, Neural Networks, NN 2011, Sparse Coding, Sparse Coding Requirement