A low power design on diffusive interconnection large-neighborhood cellular nonlinear network for giga-scale system application

A diffusive interconnection large-neighborhood cellular nonlinear (neural) network (LN-CNN) with low power dissipation and small chip area is proposed and analyzed. In the proposed new architecture, the number of gain blocks can be reduced by merging template A and template B models with suitable adjustment. All the gain blocks are based on simple current-mirror circuits so the cell has small chip area to save more power. Thus, the new architecture and circuits are suitable for large array LN-CNN implementation for giga-scale system applications. The functions of LN-CNN are verified by HSPICE simulation and the LN-CNN chip will be fabricated to verify the simulation results.