A Massively Parallel Associative Memory Based on Sparse Neural Networks

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Provided by: McGill University
Topic: Storage
Format: PDF
Associative memories store content in such a way that the content can be later retrieved by presenting the memory with a small portion of the content, rather than presenting the memory with an address as in more traditional memories. Associative memories are used as building blocks for algorithms within database engines, anomaly detection systems, compression algorithms, and face recognition systems. A classical example of an associative memory is the Hopfield neural network. Recently, the researchers have introduced an alternative construction which builds on ideas from the theory of error correcting codes and which greatly outperforms the Hopfield network in diversity, capacity and efficiency.
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