Integer-weight neural nets
A.H. Khan, Evor L. Hines · Electronics Letters · 1994
Integer-weight neural nets (IWNN) are better suited for hardware implementation than their real-weight analogues. The authors present a learning procedure for generating multilayer IWNNs having all weights in the set {–3, –2, –1, 0, 1, 2, 3}. The performance of this procedure was evaluated on XOR, encoder/decoder and the MONK benchmark. The IWNNs were found to be as capable as their real-weight counterparts with regard to generalisation performance.