Abstract A great deal of interest has emerged recently in the field of Boolean neural networks. Boolean neural networks require far less training than the conventional neural networks and have a variety of applications. They are also strong candidates for VLSI design. In this paper, a technique for learning representation of an adder-subtractor cell has been proposed. The technique can be exploited for the VLSI design of an arithmetic unit for a pipelined digital computer.