Design of a parallel neural processor

The goal of this work is to design a neural processor that compute in a efficient way a Feed-Forward Neural Network. It was accomplished by the design of an optimized product-sum architecture and a microcontroller based on the data flow theory. The architecture proposed is faster than some computer implementations like MatLab(R) 4.2. Neural Network Toolbox and language "C" program.