Sliding window with large amounts of data

I am looking at finding a window amongst tens of thousands of data points that fits a certain criteria, peak-to-peak < 10 for example. What is the best approach to this? I was thinking of doing a sliding window but to make sure I am able to find all solutions i will need to increment the window by 1 data point for each loop. What functions could potentially help me with this?

[Peng Li]

Will your window length be a fixed number or not?

[Ryan Gutierrez]

Yes it will.

Answer 1

[Walter Roberson]

https://www.mathworks.com/help/images/ref/colfilt.html with 'sliding' option.

Or blockproc() with careful control of borders.

But sometimes the easiest / fastest approach is to use conv(), possibly multiple times. Note that filtering operations involving max() or min() over a window can be handled by some of the morphology processes in the Image Processing Toolbox.