FPGA Parallel Implementation of CMAC Type Neural Network with on Chip Learning

Abstract

The hardware implementation of neural networks is a new step in the evolution and use of neural networks in practical applications. The CMAC cerebellar model articulation controller is intended especially for hardware implementation, and this type of network is used successfully in the areas of robotics and control, where the real time capabilities of the network are of particular importance. The implementation of neural networks on FPGA's has several benefits, with emphasis on parallelism and the real time capabilities. This paper discusses the hardware implementation of the CMAC type neural network, the architecture and parameters and the functional modules of the hardware implemented neuro-processor.