Neural control based on RBF network implemented on FPGA

Abstract

The RBF radial basis function network 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 has several benefits, with emphasis on parallelism and the real time capabilities. This paper discusses the hardware implementation of the RBF type neural network, the architecture and parameters and the functional modules of the hardware implemented neuro-processor.