Neural Network Learns SDR Ham Radio:

Identifying ham radio signals used to be easy. Beeps were Morse code, voice was AM unless it sounded like Donald Duck in which case it was sideband. But there are dozens of modes in common use now including TV, digital data, digital voice, FM, and more coming on line every day. [Randaller] used CUDA to build a neural network that could interface with an RTL-SDR dongle and can classify the signals it hears. Since it is a neural network, it isn't so much programmed to do it as it is trained. The proof of concept has training to distinguish FM, SECAM, and tetra. However, you can train it to recognize other modulation schemes if you want to invest the time into it.

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