| A behavior model-based software simulations of a biologically inspired neuromorphic chip are presented. The model includes nanoscale nonvolatile memory cell characteristics as synapse. A CMOS analog digital mixed circuits are prepared as neuron function models. In the simulation, the synapse between pre- and post- neurons is expressed with model based on spike timing dependent plasticity (STDP) learning rule. A pattern learning and recognition simulation shows one of the most promising approach for silicon implementation of spiking neurons with plastic synapses which enable STDP learning. The result also indicates a sensitivity problem. A solution for the mitigation is also proposed. |