Recurrent networks that perform a winner-take-all computation have been studied extensively. Although some of these studies include spiking networks, they consider only analog inputs. We present results from an analog VLSI implementation of a winner-take-all network that receives spike trains as input. We show how we can configure the connectivity in the network so that the winner is selected after a predetermined number of input spikes. To reduce the effect of transistor mismatch on the network operation, we use bursts of input spikes to compensate for this mismatch. The chip with a network of 64 integrate-and-fire neurons can reliably detect the winning neuron, that is, the neuron that receives spikes with the shortest inter-spike interval.
['Matthias Oster', 'Shih-Chii Liu']
A winner-take-all spiking network with spiking inputs