Circuit realization of a programmable neuron transfer function and its derivative
Chun Lu, Bingxue Shi · 2000
In on-chip back-propagation learning neural networks, both a sigmoidal transfer function and its derivative are required. A simple CMOS analog neuron circuit that can realizes both functions is proposed. The neuron is widely applicable because of its programmability. Based on this novel neuron, a two-layer feedforward artificial neural network (ANN) is designed. HSPICE simulation results has proved its ability to solve the XOR problem.