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oliver_quartic

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I'm sure this was fun to build, but it doesn't sound particularly practical.

Specifically, it's unclear why one would eschew the high degree of structure in OFDM (specifically designed to aid analytical approaches to time/frequency/channel estimation) in place of applying a general-purpose learning technique.

I suspect this results in a much lower-performing, much more expensive algorithm, relative to state of the art. The lack of a relative performance comparison is telling here. (Detection "below the noise floor" sounds impressive, but in practice that's how many/most digital radio systems work.)

It's also unclear whether this actually provides fine time/frequency offset estimates. These are the numbers one actually needs, not just "was there a signal".

Couple of things:

1. "Call/pass by XXX" terminology usually refers to language semantics, not underlying implementation details. In that respect, the call-stack mechanism is largely orthogonal here.

2. According to this oft-cited article (in the context of Java), passing an address under the hood is not sufficient to make a language call-by-reference. http://javadude.com/articles/passbyvalue.htm - AFAIK Python would "fail" the "Litmus test".

(EDIT - clarify what's not call-by-ref)