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 🙂
here is the link: https://ecmiindmath.org/2018/01/29/studying-uncertainty-for-robot-localization-with-multiple-sensors-using-monte-carlo-localization/
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.
Check out this page to follow on.
So, I finally started to create the LabVIEW content. Check out the page here! Introduction material has been added.
DIP is one emerging technology that is getting a lot of applications in various fields. It has its origins dating back to the early 20th century where it had a sole application in the press sector. Nowadays, it exists in photography, medicine, industry and astronomy. So, what do we mean by DIP and how do we see an image from an engineering perspective?
Find out here