Reservoir expansion can improve online independent component analysis (ICA) under nonlinear mixing, yet top-$n$ whitening may discard injected features. We formalize this bottleneck as \emph{reservoir subspace injection} (RSI): injected features help only if they enter the retained eigenspace without displacing passthrough directions. RSI diagnostics (IER, SSO, $ρ_x$) identify a failure mode in our top-$n$ setting: stronger injection increases IER but crowds out passthrough energy ($ρ_x: 1.00\!\rightarrow\!0.77$), degrading SI-SDR by up to $2.2$\,dB. A guarded RSI controller preserves passthrough retention and recovers mean performance to within $0.1$\,dB of baseline $1/N$ scaling. With passthrough preserved, RE-OICA improves over vanilla online ICA by $+1.7$\,dB under nonlinear mixing and achieves positive SI-SDR$_{\mathrm{sc}}$ on the tested super-Gaussian benchmark ($+0.6$\,dB).

翻译：储层扩展可改善非线性混合下的在线独立成分分析（ICA），但Top-$n$白化可能丢弃注入特征。我们将此瓶颈形式化为\emph{储层子空间注入}（RSI）：注入特征仅当其进入保留特征空间且不置换直通方向时才能发挥作用。RSI诊断指标（IER、SSO、$ρ_x$）揭示了Top-$n$设定中的失效模式：增强注入会提升IER指标，但会挤占直通能量（$ρ_x: 1.00\!\rightarrow\!0.77$），导致SI-SDR最多下降$2.2$\,dB。采用防护型RSI控制器可保持直通保留，将平均性能恢复至基线$1/N$缩放的$0.1$\,dB范围内。在保持直通特性的前提下，RE-OICA较基础在线ICA在非线性混合下提升$+1.7$\,dB，并在测试的超高斯基准上实现正向SI-SDR$_{\mathrm{sc}}$（$+0.6$\,dB）。