Hardware implementation of a MLP network with on-chip learning

In this paper we propose a method to implement in FPGA circuits, a feedforward neural network with on-chip delta rule learning algorithm. The method implies the building of a neural network by generic blocks designed in Mathworks' Simulink environment. The main characteristics of this solution are on-chip learning algorithm implementation and high reconfiguration capability and operation under real time constraints.