Spatial pattern formation via reaction-diffusion dynamics in 32 * 32 * 4 CNN chip

Reaction-diffusion dynamics have been proposed to explain pattern-formation behavior in a variety of systems, e.g., chemical and biological. This paper describes a cellular neural network chip that exhibits spatially organized patterns of activity, which are formed by reaction diffusion. The chip contains four 32 * 32 cell arrays of transistors which are locally coupled and operate in weak inversion. Typical patterns consist of alternating regions of high- and low-drain currents with a preferred width, but no preferred orientation. Experimental, theoretical, and simulation results for this chip are in complete concordance, demonstrating that conventional very large-scale integration technology can be an ideal substrate for studying the spatiotemporal dynamics and applications of reaction-diffusion. The chip, which was fabricated in a 0.5-(mu)m process, settles to steady-state patterns within several hundred microseconds and dissipates 10.55 mW.