A Gaussian synapse circuit for analog VLSI neural networks

Back-propagation neural networks with Gaussian function synapses have a better convergence property over those with linear-multiplying synapses. A compact analog Gaussian synapse cell which is not biased in the subthreshold region has been designed for fully-parallel operation. This cell can approximate a Gaussian function with accuracy around 98% in the ideal case. Device mismatch induced by fabrication process will cause some degradation to this approximation. Programmability of the proposed Gaussian synapse cell is achieved by changing the stored synapse weight W_ji, the reference current and the sizes of transistors in the differential pair