Biologically Inspired Neural Networks and Dynamic Learning onto CMOS/nanowire/MOLecular (CMOL) Architecture

Self assembly molecular (nano) devices have good properties for implementing synapses in defect tolerant neural network circuits. Here we proposed a system configuration and a model of STDP learning method, in which the CMOL-based hardware platform can be used to implement biologically inspired Spiking Neural Networks (SNNs) with dynamic learning. This learning method is based on spatially and temporally local synaptic information, that is available at the synapse at the time of synaptic modification and can map it to the CMOL hardware