Learned adaptive properties for mitigation of weight perturbations in embedded spiking networks.

In feedforward networks (top) the perturbed model showed a trend of performing better for moderate perturbation levels when trained at high levels of perturbation, but at the cost of low-perturbation performance, and never achieved greater than 50% accuracy for test perturbation levels above 0.3.

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