Roshan Gopalakrishnan

Learn More
This brief describes the neuromorphic very large scale integration implementation of a synapse utilizing a single floating-gate (FG) transistor that can be used to store a weight in a nonvolatile manner and demonstrate biological learning rules such as spike-timing-dependent plasticity (STDP). The experimental STDP plot (change in weight against ∆t=tpost -(More)
Synapse plays an important role in learning in a neural network; the learning rules that modify the synaptic strength based on the timing difference between the pre- and postsynaptic spike occurrence are termed spike time-dependent plasticity (STDP) rules. The most commonly used rule posits weight change based on time difference between one presynaptic(More)
— Synapse plays an important role of learning in a neural network; the learning rules which modify the synaptic strength based on the timing difference between the pre-and postsynaptic spike occurrence is termed as Spike Time Dependent Plasticity (STDP). The most commonly used rule posits weight change based on time difference between one presynaptic spike(More)
  • 1