Purin: A Biology-inspired Mechanism for Artificial Neural Networks

Purin is a biology-inspired mechanism for artificial neural networks that adds synaptic efficacy modulation to conventional convolutional neural networks. It introduces a time‑interval‑based abstraction for neural activities, allowing short‑ and long‑term synaptic efficacy changes without discrete time‑steps. Experiments on AlexNet, VGG11, and GoogLeNet show that Purin improves classification accuracies across evaluated datasets.

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