clean_channels() leads to different channel removed results when using parallel processing

[leima1]

Description

This is more a minor suggestion than a bug report. When running clean_channels() using parallel processing, each worker uses an independent random number stream. This causes reproducibility issues when re-running the analysis with parallel processing (i.e., the same worker might not be assigned to run the same subject or trial when clean_channels() called, leading to a different outcome for that subject or trial).

According to https://www.mathworks.com/help/parallel-computing/control-random-number-streams-on-workers.html, setting rng(0, 'Philox'), instead of rng('default') ensures that all workers use the same random number generator. In our experience, replacing that line within clean_channels() has stabilized the channel removal results across repeated runs.

#### Versions

OS version	[Windows 10]
Matlab version	[2023b]
EEGLAB version	[2025]