CURRENT-MODE HAMMING NEURAL NETWORK

A current-mode Hamming neural network is provided with N binary inputs, and has a template matching calculation subnet and a winner-take-all subnet. The template matching calculation subnet includes M first neurons in which M exemplar templates are stored respectively. Each first neuron is consisted of current mirrors connected to and controlled by the N binary inputs respectively, to generate a template matching current signal which is substantially proportional to the number of matched bits between the N binary inputs and the corresponding stored exemplar template. The winner-take-all subnet includes M second neurons, each including M transistors with their gate electrodes connected together to form a template competition node, their source electrodes connected to ground, and their drain electrodes connected to the template competition nodes respectively. The template competition nodes are coupled to and receive the template matching current signals respectively, so that the template competition node connecting with the largest template matching current signal is eventually at a relatively high voltage level, and the other template competition nodes are at a relatively low voltage level, after competition.