Hardware implementation of a mixed analog-digital neural network
This paper describes a hardware implementation of a firing neural network based on the models of Gerstner. It mainly consists of analog building blocks (neurons, synapses), but because of their digital interface and controlling it is a mixed-mode structure. The complete physical implementation of all components allows massive parallel and real time computation. The input data processing is located off-chip to enlarge the number of implementable neural networks.