Memristor based crossbars drew attention by computing the vector-matrix calculation intensive tasks such as AI and ML in one time-step. Although they provide an energy efficient way of computing these tasks, analog computation in general suffers from non-idealities and systematic errors in the circuitry which could degrade the performance and accuracy significantly. One of the issues is the random offset associated with the op-amps in the system resulting from the process and mismatch variations. In this paper, a novel technique is offered to reduce the negative effects of the random offset and increase the output accuracy. This newly proposed system uses minimum extra circuitry and additional power consumption and only requires the crossbar to be enlarged by two extra rows. The effectiveness of the offered technique demonstrates a 6x better accuracy with the mitigation of the offset problem. The proposed method can be used in memristor and other analog crossbars to achieve a greater performance and thus improve their competitiveness.