Abstract
A generalized bell-shaped function is an essential building block for a neuro-fuzzy systems and radial basis function neural networks. With the advent of edge computing, analog neuro-chips can potentially speed-up the near sensor computing. In this paper, we present a generalized bell function generator circuit for machine learning architectures. The circuit design of generalized bell-shaped function as the hybrid CMOS-Memristor that is compatible with typical memristive crossbar architecture is presented, where it uses three memristors to control the output current shape. Designed circuit occupies 10 μm2and consumes less than 4.1 μW. The proposed circuit could be used as a standalone neuron for radial basis function neural network, as demonstrated in this work.