9×9 DPCNN board: A multichip approach to CNN implementation

Among artificial neural network architectures, the Cellular Neural Networks represent one of the most attractive from a VLSI point of view. The 3×3 DPCNN chip, formerly presented by the authors, is a very effective implementation of CNN´s. This paper presents a multichip 9×9 CNN board which is made up of nine 3×3 DPCNN chips. The board is fully programmable by a Personal Computer which enables the selection of the parameters of the network and the steady-state voltages acquisition. The system PC/9×9CNN board represents a very powerful tool in the investigation of new CNN algorithms as well as their dynamic behaviours