Online, real-time learning in neuromorphic circuits have been implemented through variants of Spike Time Dependent Plasticity (STDP). Current implementations have used either floating-gate devices or memristors to implement such learning synapses together with non-volatile storage. However, these approaches require high voltages (3- 12V) for weight update and entail high energy for learning (4- 30pJ/write.
SNN consists of spiking neurons that do not generate outputs at each time step like other artificial neutral networks. Instead, a neuron produces a spike asynchronously when
its membrane potential (Vm) reaches a specific value. The information transfer in SNN hence takes place through precise spiking time or rates of spikes.
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ynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture.pdf