Abstract: A non-linear signal classifier (26) includes a polynomial expansion unit for expanding signal feature vectors determined by a feature extraction unit (25) for a received signal. The expanded signal feature vectors are each combined with a plurality of signal classification models that are stored in a model memory (76). The signal classification models are each associated with a particular signal type that is recognized by the non-linear signal classifier. A scoring unit (72) generates a score for each of the signal classification models based on the result of the combination. The scores are analyzed by a selection unit (74) which determines which of the signal classification models (i.e., which of the signal types) most likely represents the received signal. Training equipment (60) is also provided for training the non-linear signal classifier (26) to recognize new signal types.