Synthesis of a recurrent double-layer transistor network for early-vision tasks

In this paper we present a double-layer transistor network, useful for early-vision embedded systems, able to convolve a sensorial input with a Gabor kernel. The network, whose main advantages are low power consumption, compactness of physical implementation and full programmability of the convolution kernel, has been simulated and successfully compared with theoretical expectations