Publication: Spiking LCA in a Neural Circuit with Dictionary Learning and Synaptic Normalization
Spiking LCA in a Neural Circuit with Dictionary Learning and Synaptic Normalization
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Chavez Arana, D., Renner, A., & Sornborger, A. (2023). Spiking LCA in a Neural Circuit with Dictionary Learning and Synaptic Normalization. Proceedings of the Neuro-Inspired Computational Elements Conference, 47–51. https://doi.org/10.1145/3584954.3584968
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The Locally Competitive Algorithm (LCA) [17, 18] was put forward as a model of primary visual cortex [14, 17] and has been used extensively as a sparse coding algorithm for multivariate data. LCA has seen implementations on neuromorphic processors, including IBM’s TrueNorth processor [10], and Intel’s neuromorphic research processor, Loihi, which show that it can be very efficient with respect to the power resources it consumes [8]. When combined with dictionary learning [13], the LCA algorithm encounters synaptic instability [24], wh
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- Chavez Arana, Diego
- Renner, Alpha
- Sornborger, Andrew
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Chavez Arana, D., Renner, A., & Sornborger, A. (2023). Spiking LCA in a Neural Circuit with Dictionary Learning and Synaptic Normalization. Proceedings of the Neuro-Inspired Computational Elements Conference, 47–51. https://doi.org/10.1145/3584954.3584968
