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Wrote results for pipeline_full, pipeline_short, and feat_cross_species.

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j-hartling
2026-05-07 18:15:00 +02:00
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\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces \textbf {Rectification and lowpass filtering improves SNR but does not contribute to intensity invariance.} Input $x_{\text {raw}}(t)$ consists of song component $s(t)$ scaled by $\alpha $ with optional noise component $\eta (t)$ and is successively transformed into tympanal signal $x_{\text {filt}}(t)$ and envelope $x_{\text {env}}(t)$. Different line styles indicate different cutoff frequencies $f_{\text {cut}}$ of the lowpass filter extracting $x_{\text {env}}(t)$. \textbf {Top}:~Example representations of $x_{\text {filt}}(t)$ and $x_{\text {env}}(t)$ for different $\alpha $. \textbf {a}:~Noiseless case. \textbf {b}:~Noisy case. \textbf {Bottom}:~Intensity metrics over a range of $\alpha $. \textbf {c}:~Noiseless case: Standard deviations $\sigma _x$ of $x_{\text {filt}}(t)$ and $x_{\text {env}}(t)$. \textbf {d}:~Noisy case: Ratios of $\sigma _x$ of $x_{\text {filt}}(t)$ and $x_{\text {env}}(t)$ to the respective reference standard deviation $\sigma _{\eta }$ for input $x_{\text {raw}}(t)=\eta (t)$. \textbf {e}:~Ratios of $\sigma _x$ to $\sigma _{\eta }$ of $x_{\text {env}}(t)$ as in \textbf {d} for different species (averaged over songs and recordings, see appendix Fig.\,\ref {fig:app_rect-lp}). }}{12}{}\protected@file@percent }
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