Holographic Graph Neuron: A Bioinspired Architecture for Pattern Processing.
basic_science · Level V
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- Record sourced from PubMed, PMID 26978836.
- Also identified by DOI 10.1109/TNNLS.2016.2535338.
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Abstract
In this paper, we propose a new approach to implementing hierarchical graph neuron (HGN), an architecture for memorizing patterns of generic sensor stimuli, through the use of vector symbolic architectures. The adoption of a vector symbolic representation ensures a single-layer design while retaining the existing performance characteristics of HGN. This approach significantly improves the noise resistance of the HGN architecture, and enables a linear (with respect to the number of stored entries) time search for an arbitrary subpattern.