An analog implementation of discrete-time cellular neural networks

Abstract
An analog circuit structure for the realization of discrete-time cellular neural networks (DTCNNs) is introduced. The computation is done by a balanced clocked circuit based on the idea of conductance multipliers and operational transconductance amplifiers. The circuit is proposed for a one-neighborhood on a hexagonal grid, but can also be modified to larger neighborhoods and/or other grid topologies. A layout was designed for a standard CMOS process, and the corresponding HSPICE simulation results are given. A test chip containing 16 cells was fabricated, and measurements of the transfer characteristics are provided. The functional behavior is demonstrated for a simple example.

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