John May

Dr. John May

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16 years, 16 days
Maplesoft
Pasadena, California, United States

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I have been a part of the Mathematical Software Group at Maplesoft since 2007. I have a Ph.D in Mathematics from North Carolina State University as well as Masters and Bachelors degrees from the University of Oregon. I have been working on research in computational mathematics since 1997. I currently work on symbolic solvers and visualization as well as other subsystems of Maple.

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These are Posts that have been published by John May

If you are interested in listing to me ramble for an hour about integration algorithms, it looks like the recording of the Webinar I gave in early September has been posted to the academic webinar archive: Theory and Practice of Symbolic Integration in Maple. I tried to make it a broad introduction for someone with...

I have gotten some comments about my new avatar, including a few commenting that while my picture is clear on the blog contributors sidebar, it is "blurry" on my blog posts. I just wanted clear this up.  I am not in the witness protection program; I just really love singular values.  My new avatar, just like my old one, is a rank 4 approximation of a picture of me using the singular value decomposition.

In a series of posts now imported to the Maplesoft blog (starting here), I have been talking about pseudo-random number sequences, but since part of what kicked off this series was a paper on true random number generation (with LASERS!) I thought I would share some routines I wrote that alllow you to use the two main true random number sources available on the web (neither using lasers, sadly).

In this post I'll introduce is a nice visual test of randomness from signal processing. The main idea of this test to look at how a random sequence correlates with itself.

It's been a while since I wrote one of these random posts, but I still have a couple more I wanted to write.  In this post, I want to describe one of the tests used in the paper that initially inspired this series of posts: the Wald-Wolfowitz runs test.  This test is interesting in that it does not test for uniformity

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