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Faster sliding window statistics?

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K E
K E 2016 年 10 月 13 日
編集済み: K E 2016 年 10 月 14 日
I use slidefun to estimate statistics such as max, min, or RMS within a sliding window applied to a time series. It is very useful, but it can be slow if there are a lot of data points. Is there a faster sliding window routine out there? I didn't see any obvious candidates in the File Exchange, but would like to know if I missed any.

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採用された回答

Steven Lord
Steven Lord 2016 年 10 月 13 日
If you're using release R2016a or later, consider using the moving statistics functions in MATLAB for at least min and max.
Depending on exactly what type of windows you're using, if you're using release R2016b storing your data in a timetable and using the retime function with an aggregation method is another potential option.

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K E
K E 2016 年 10 月 14 日
On my machine: with movmin , 0.7s. With slidefun, 310s. This is really going to streamline a lot of work for me & my coworkers.

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その他の回答 (1 件)

Image Analyst
Image Analyst 2016 年 10 月 13 日
You can use these alternate functions. For mean, use conv(). For max, use imdilate(). For min use imerode(). Or the new moving stats functions Steve mentioned. They're all highly optimized. Whether they're faster than slidefun() is something you'll just have to check.

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K E
K E 2016 年 10 月 14 日
Unfortunately I do not have the Image Processing Toolbox, but I am sure these would be faster.

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