The calibration of a 2-D displacement sensor that suffers from nonlinearities and cross talking using an Artificial Neural Networks (ANN) is described. The ANN is used as a Pattern Associator that is trained to perform the mapping between the sensor''s readings and the actual sensed properties. For comparison purposes a few methods were explored: 1 ) A three-layer ANN with a different number of hidden units trained by the Back Propagation (BP) method 2) Cerebellar Model Arithmetic Computer (CMAC) with a fixed number of quantizing functions and 3) Polynomial curve fitting technique. The results of the calibration procedure and recommendations are discussed. 2.