Voiceband signal classification using statistically optimal combinations of low-complexity discriminant variables

This paper considers the problem of classifying voiceband modem, facsimile, native binary data, and speech signals on a 64-kb/s digital channel using low complexity discriminant functions similar to those investigated by Benvenuto (1989). Benvenuto's method is simplified by replacing an approximate demodulation step with rectification of the passband signal and improved by using statistical analysis to select and combine the most effective variables into statistically optimal discriminant functions.