Abstract
In this paper, we highlight how computational properties of biological dendrites can be leveraged for neuromorphic applications. Specifically, we demonstrate analog silicon dendrites that support multiplication mediated by conductance-based input in an interception model inspired by the biological dragonfly. We also demonstrate spatiotemporal pattern recognition and direction selectivity using dendrites on the Loihi neuromorphic platform. These dendritic circuits can be assembled hierarchically as building blocks for classifying complex spatiotemporal patterns.
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CITATION STYLE
Cardwell, S. G., & Chance, F. S. (2023). Dendritic Computation for Neuromorphic Applications. In ACM International Conference Proceeding Series. Association for Computing Machinery. https://doi.org/10.1145/3589737.3606001
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