Closed MattCarrickPL closed 2 months ago
Internal discussion resulted in the outcome that while the magnitude of the DC offset isn't practical from a DSP & RF sense, the extremeness of it is useful for training the ML algorithm so the effect will stay. However, the distribution of the magnitude needs to be log-normal such that the ML most commonly experiences practical values but it does experience extreme values but with less frequency.
Large spike near DC may also be the result of the quantize() transform. Requires additional investigation.
DC offset magnitude appears to be too large in relation to noise floor & signal.
The range of values for the magnitude (in dB) of the DC offset is defined here, which is -0.1 to +0.1: https://github.com/TorchDSP/torchsig/blob/6bd7509c54242f95de60fe4f1577bf59ace2dded/torchsig/datasets/modulations.py#L220
The amplitude is calculated via https://github.com/TorchDSP/torchsig/blob/6bd7509c54242f95de60fe4f1577bf59ace2dded/torchsig/transforms/functional.py#L825
Which for the maximum value is 10**(0.1/10) = 1.02, which roughly tracks to the time domain of the example in the attached image