its interesting how my obsession with mathematics is leading my passions and paths in life! The title, mathematician” shakens my heart, the inclusion of math into any project is an enough inspirational motivation for me, I visualize my growing dreams as an exponential graph, my perception of music can’t drift from Fourier summation of harmonics, I see people everyday on way to work as a set of vectors belonging to a commuting basis, my eyes won’t stop seeing quiver field for each geometric shape l see whether it’s the sun or pavement, a not-good sleep l feel as a sparse matrix …
I’ve always been obsessed with mathematics because the insight it gives for physics and I’ve been fond of physics for the beautiful description she offers for our universe, or maybe more, and this is true thanks to great minds like you, sir! Stephen #Hawking has always inspired me to learn, wonder and open my eyes to the charming cosmos around us. His books, lectures and even the movie have constituted a vast basis of myself, my passion and my perception of the world; a basis that founded many vectors for education, activities and career …
You left us on Pi day, just like how Einstein boarded z science deck!
Happy Pi day and RIP, Hawking 😦 ❤
So, I got my “Studying Uncertainty for robot localization using Monte Carlo Localization” project posted in ECMI (European Consortium for Mathematics in Industry) blog 🙂
So what about ciphering text message using LabVIEW? In this tutorial, we explore using ROT13 in LabVIEW; check it here!
Make sure to also check LabVIEW main page here.
Now, it’s time to play around with audio files inside LabVIEW. It’s always pretty cool to play with music. So, let’s try out and have some fun playing back the music, plotting it on a graph and do Fourier Transform to see the frequencies chart. Check out here.
The next practice of using LabVIEW is out! In this one, we will apply the previous VI into something practical. Let’s build a Fourier summation. If you don’t remember, then any function (not quite any function, but let’s skip the theory for now) can be represented by Fourier approximation as:
f(x) = ∑a cos (nx) + b sin(nx)
In this formula, a and b are the Fourier coefficients that can be calculated using some equations, but for simplification purposes we will enter them manually.
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