  This paper presents a classification model for microphone type recognition in
photoacoustic experiment. The classification model is obtained by applying a
multilayer perceptron network on a large dataset of simulated experimental
values. The model satisfies the basic requirements of a photoacoustic
experiment: accuracy, reliability and real time operations.
