Automatic general-purpose neural hardware generator

Artificial neural networks have a wide range of applications. In some applications, specific hardware is necessary when a PC cannot be connected or due to other factors such as speed, price and fault tolerance. The difficulty in producing hardware for neural networks is associated with price, accuracy and development time. Most users also prefer the network trained with a high-level tool without reducing resolution and simplifying the activation function for hardware implementation. This paper proposes an automatic general-purpose neural hardware generator, simple to use, with adjustable accuracy that provides direct hardware implementation for neural networks with FPGAs without further development.