Abstract
In the design of a specific application requiring scalar processing and a neural network, it was noticed that the same underlying hardware used to process analog signals could be used as another way to implement neural networks. This paper presents the main ideas behind this design approach, and a comparison in terms of area and processing speeds of both solutions, when using an FPGA as a substrate.