Cross-checked and polished remainders of fig_invariance_thresh_lp_species.pdf.
Added misc_functions.py for anything not plot-related.
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main.aux
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main.aux
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\newlabel{eq:toy_log}{{12}{11}{}{}{}}
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\newlabel{eq:toy_highpass}{{13}{11}{}{}{}}
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\newlabel{eq:toy_snr}{{14}{12}{}{}{}}
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\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces \textbf {Intensity invariance by logarithmic compression and adaptation is restricted by the noise floor.} Synthetic input $x_{\text {filt}}(t)$ consists of song component $s(t)$ scaled by $\alpha $ with (\textbf {c}{} and \textbf {d}) or without (\textbf {a}{} and \textbf {b}) additive noise component $\eta (t)$. Input $x_{\text {filt}}(t)$ is transformed into envelope $x_{\text {env}}(t)$, logarithmically compressed envelope $x_{\text {dB}}(t)$, and intensity-adapted envelope $x_{\text {adapt}}(t)$. \textbf {Left}:~$x_{\text {env}}(t)$, $x_{\text {dB}}(t)$, and $x_{\text {adapt}}(t)$ for different scales $\alpha $. \textbf {Right}:~Ratios of the standard deviation of $x_{\text {env}}(t)$, $x_{\text {dB}}(t)$, and $x_{\text {adapt}}(t)$ relative to the respective reference standard deviation $\sigma _{\eta }$ for input $x_{\text {filt}}(t)=\eta (t)$. \textbf {a}{} and \textbf {b}:~Ideally, if $x_{\text {filt}}(t)=\alpha \cdot s(t)$, then $x_{\text {adapt}}(t)$ is intensity-invariant across all $\alpha $. \textbf {c}{} and \textbf {d}:~In practice, if $x_{\text {filt}}(t)=\alpha \cdot s(t)+\eta (t)$, the intensity invariance of $x_{\text {adapt}}(t)$ is limited to sufficiently large $\alpha $. Shaded area indicates saturation of $x_{\text {adapt}}(t)$ at $95\,\%$ curve span. }}{12}{}\protected@file@percent }
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\newlabel{fig:inv_log-hp}{{4}{12}{}{}{}}
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\@writefile{lof}{\contentsline {figure}{\numberline {5}{\ignorespaces \textbf {Intensity invariance by thresholding and temporal averaging depends on both the threshold value and the noise floor.} Synthetic input $x_{\text {adapt}}(t)$ consists of song component $s(t)$ scaled by $\alpha $ with additive noise component $\eta (t)$. Input $x_{\text {adapt}}(t)$ is transformed into kernel response $c_i(t)$, binary response $b_i(t)$, and feature $f_i(t)$. Threshold value $\Theta _i$ is set to multiples of the reference standard deviation $\sigma _{\eta }$ of $c_i(t)$ for input $x_{\text {adapt}}(t)=\eta (t)$. Darker colors correspond to higher $\Theta _i$. \textbf {Left}:~$x_{\text {adapt}}(t)$, $c_i(t)$, $b_i(t)$, and $f_i(t)$ for different scales $\alpha $ and threshold values $\Theta _i$. Left-most column is is the pure-noise reference. \textbf {Right}:~Average value of $f_i(t)$ during the song for the different $\Theta _i$. \textbf {a}:~Input $x_{\text {adapt}}(t)$. \textbf {b}-\textbf {d}:~$c_i(t)$, $b_i(t)$, and $f_i(t)$ for the different $\Theta _i$ based on the same $x_{\text {adapt}}(t)$ from \textbf {a}{}. \textbf {e}:~Average value of $f_i(t)$ during the song for the different $\Theta _i$ in \textbf {b}{}-\textbf {d}. }}{13}{}\protected@file@percent }
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\newlabel{fig:inv_thresh-lp_full}{{7}{14}{}{}{}}
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\newlabel{eq:pdf_split}{{15}{14}{}{}{}}
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\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces \textbf {Intensity invariance by logarithmic compression and adaptation is restricted by the noise floor.} Synthetic input $x_{\text {filt}}(t)$ consists of song component $s(t)$ scaled by $\alpha $ with (\textbf {c}{} and \textbf {d}) or without (\textbf {a}{} and \textbf {b}) additive noise component $\eta (t)$. Input $x_{\text {filt}}(t)$ is transformed into envelope $x_{\text {env}}(t)$, logarithmically compressed envelope $x_{\text {dB}}(t)$, and intensity-adapted envelope $x_{\text {adapt}}(t)$. \textbf {Left}:~$x_{\text {env}}(t)$, $x_{\text {dB}}(t)$, and $x_{\text {adapt}}(t)$ for different scales $\alpha $. \textbf {Right}:~Ratios of the standard deviation of $x_{\text {env}}(t)$, $x_{\text {dB}}(t)$, and $x_{\text {adapt}}(t)$ relative to the respective reference standard deviation $\sigma _{\eta }$ for input $x_{\text {filt}}(t)=\eta (t)$. \textbf {a}{} and \textbf {b}:~Ideally, if $x_{\text {filt}}(t)=\alpha \cdot s(t)$, then $x_{\text {adapt}}(t)$ is intensity-invariant across all $\alpha $. \textbf {c}{} and \textbf {d}:~In practice, if $x_{\text {filt}}(t)=\alpha \cdot s(t)+\eta (t)$, the intensity invariance of $x_{\text {adapt}}(t)$ is limited to sufficiently large $\alpha $. Shaded area indicates saturation of $x_{\text {adapt}}(t)$ at $95\,\%$ curve span. }}{13}{}\protected@file@percent }
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\@writefile{lof}{\contentsline {figure}{\numberline {5}{\ignorespaces \textbf {Intensity invariance by thresholding and temporal averaging depends on both the threshold value and the noise floor.} Synthetic input $x_{\text {adapt}}(t)$ consists of song component $s(t)$ scaled by $\alpha $ with additive noise component $\eta (t)$. Input $x_{\text {adapt}}(t)$ is transformed into kernel response $c_i(t)$, binary response $b_i(t)$, and feature $f_i(t)$. Threshold value $\Theta _i$ is set to multiples of the reference standard deviation $\sigma _{\eta }$ of $c_i(t)$ for input $x_{\text {adapt}}(t)=\eta (t)$. Darker colors correspond to higher $\Theta _i$. \textbf {Left}:~$x_{\text {adapt}}(t)$, $c_i(t)$, $b_i(t)$, and $f_i(t)$ for different scales $\alpha $ and threshold values $\Theta _i$. Left-most column is is the pure-noise reference. \textbf {Right}:~Average value of $f_i(t)$ during the song for the different $\Theta _i$. \textbf {a}:~Input $x_{\text {adapt}}(t)$. \textbf {b}-\textbf {d}:~$c_i(t)$, $b_i(t)$, and $f_i(t)$ for the different $\Theta _i$ based on the same $x_{\text {adapt}}(t)$ from \textbf {a}{}. \textbf {e}:~Average value of $f_i(t)$ during the song for the different $\Theta _i$ in \textbf {b}{}-\textbf {d}. }}{14}{}\protected@file@percent }
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\abx@aux@cite{0}{stumpner1991auditory}
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\abx@aux@segm{0}{0}{stumpner1991auditory}
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