Coughing is one of the most frequent overt symptoms of many diseases affecting the airways and lungs of man and other animals. The registration of the cough sound as a diagnostic tool is still absent from current medical and veterinary practice in comparison with the registration of ECG, EEG etc. Registration of coughs from four different pigs in a metallic chamber was performed in order to analyse the acoustical signals. In order to build a system that is capable of distinguishing coughs from other sounds a large number of samples were collected. The best performance was obtained with a hybrid classifier that classifies coughs and metal clanging separately from the rest, giving better results compared to a PNN (Probabilistic Neural Network) and an MLP (Multilayer Perceptron). The hybrid classifier gave high discrimination performance (91.3 %) in the case of runts and noise and a performance of 94.8% for correct classification in the case of coughs. In the case of metal clanging, 82.6 % for correct classification was obtained. The intelligent system is proposed for real-time cough registration in a pighouse, as an early alarm for possible viral infection, or for studying the pig behaviour.