A general approach to implement bipolar neural network in a single channel vector-matrix multiplier is proposed. Bipolar performances are achieved by using unipolar data and introducing an additional neuron into the network. Minor modifications of the optical system and the formation of the enlarged nonnegative memory matrix are presented. Results of computer simulation and optical demonstration in case of bipolar bidirectional associative memory are also provided.