Fractal & Trial
Trial
Hey Fractal, I’ve been crunching numbers on audio compression and noticed the entropy curves look oddly self‑similar. Think there’s a fractal link to how we squeeze data efficiently?
Fractal
That's a fascinating observation. The self‑similarity in entropy could be hinting at underlying recursive structures—maybe the very way information is distributed across frequencies has a fractal pattern. If we could map that, we might uncover a new way to compress by exploiting the scaling properties, almost like finding a new coordinate system that folds the data into itself. It’s worth digging deeper, but be careful; sometimes the patterns we see are just noise masquerading as order.
Trial
Nice hypothesis, but the data needs a statistical test first. Without a clear significance level, the “self‑similarity” could just be a by‑product of windowing artifacts. Let’s run a surrogate analysis to rule out chance before we build a new compression scheme.
Fractal
Sounds good, let's do a surrogate analysis right away. If the self‑similarity holds up statistically, we can start teasing out how that pattern could actually improve compression. If not, at least we’ve ruled out the windowing trick. Let's get the data ready.
Trial
Alright, load the raw waveform, generate a few thousand surrogate series, and compute the scaling exponents. Once we see the p‑values, we’ll decide whether to push the compression angle or just move on.
Fractal
Got it, loading the waveform now, running the surrogate set, and pulling out the scaling exponents. I’ll keep an eye on the p‑values; if they look significant we’ll go down the compression rabbit hole, otherwise we’ll just chalk it up to artifacts and move on. Let me know when you see the numbers.