We propose a new model-free segmentation method for idealizing ion channel recordings. This method is designed to deal with heterogeneity of measurement errors. This in particular applies to open channel noise which, in general, is particularly difficult to cope with for model-free approaches. Our methodology is able to deal with lowpass filtered data which provides a further computational challenge. To this end we propose a multiresolution testing approach, combined with local deconvolution to resolve the lowpass filter. Simulations and statistical theory confirm that the proposed idealization recovers the underlying signal very accurately at presence of heterogeneous noise, even when events are shorter than the filter length. The method is compared to existing approaches in computer experiments and on real data. We find that it is the only one which allows to identify openings of the PorB porine at two different temporal scales. An implementation is available as an R package.

中文翻译：

---

离子通道记录的异构理想化——开放通道噪声

我们提出了一种新的无模型分割方法，用于理想化离子通道记录。该方法旨在处理测量误差的异质性。这尤其适用于开放通道噪声，一般来说，无模型方法特别难以处理。我们的方法能够处理低通滤波数据，这提供了进一步的计算挑战。为此，我们提出了一种多分辨率测试方法，结合局部去卷积来解决低通滤波器。模拟和统计理论证实，即使事件短于滤波器长度，所提出的理想化也可以在存在异质噪声时非常准确地恢复基础信号。该方法与计算机实验和真实数据中的现有方法进行了比较。我们发现它是唯一一种允许在两个不同的时间尺度上识别 PorB 孔的开口。实现可用作 R 包。