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Which electrical engineering subdiscipline uses the most math? 
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#19
Nov1512, 03:21 AM

P: 59

Computer vision is very linear algebraheavy. I did a research project last spring in which I needed to take a picture with a camera, match it with a picture in a database taken by a different camera, and determine the relative rotation and translation between the two camerasjust from the pictures. My first three months of research were spent reading about linear algebra and projective geometry. Matrices are used for everything, and in my algorithm I used thinks like singular value decomposition, linear least squares, etc. (Unfortunately my code doesn't work yet :( ) The math was different from what I was used to, but interesting. Related to computer vision is image processing, which from what I hear is also linear algebra heavy. 


#20
Nov1512, 10:04 AM

P: 692

Anyway, besides controls, here are some more ideas: communications and information theory  see the following for a mathy take on digital communications (lecture notes are what you want) http://ocw.mit.edu/courses/electrica...sifall2006/ also signal processing, statistical signal processing, etc. Most EEs in those fields are required to take a fair amount of math while in grad school  where I was those folks had to take a year each of analysis and algebra (at the highest undergrad level). Some took grad math courses as well, but that was much less common. Some in these fields are required to take measuretheoretic probability, depending upon the advisor. So this can be mathematical. If that is what you want chose your graduate school and advisor carefully. the applied physics branches of ee tend to use different sorts of math. In electromagnetics you are usually solving PDEs or integral equations, either analytically or numerically. Approximation techniques are often key to gaining understanding in these types of calculuations. The analytical part uses lots of complex analysis, Green's functions, integral transform techniques, asymptotic expansions of integrals, manipulations of special functions, etc. The numerical part relies on numerical linear algebra to a large degree. best of luck, jason 


#21
Nov1512, 04:40 PM

P: 137

As an undergrad, the Heaviest math will probably be in Analog and Digital Signal Processing/Communications. Control Systems uses signal processing but less math intensive more often than not.
As a grad student, many more areas become much more mathematically involved  the biggest differences include that every subject now includes nonlinear, timevarying, and stochastic versions of what was done in undergrad. Signal Processing and DSP  Stochastic processes are added into the mix. Complex Analysis is suddenly needed. Control Systems  Nonlinear Systems become very mathematically intense  timevarying, systems, stochastic systems, all of which must be controlled. Very involving  research involves neural networks. Communications  this becomes information theory! Holy Crap! 


#22
Nov1612, 11:55 AM

P: 1,242

Quantum mechanics uses a lot of linear algebra, so if you get into the physics side of electronics, it will be there. 


#23
Nov1712, 10:52 PM

P: 59

Thank you everyone for all of the feedback, commentary and advice. I have decided to pursue control theory. It was really hard to make a decision, but it's getting to the point where I need to just pick one and I think it sounds the most interesting to me



#24
Nov1812, 04:39 PM

P: 137

http://www.youtube.com/watch?v=Z8oMbOj9IWM 


#25
Nov1812, 04:46 PM

P: 59

Thanks for the videos, I think they should help me. I'm glad you're happy with your choice of field. 


#26
Nov2012, 12:23 AM

P: 137

I have limited abilities at this point as well, but they will grow over the next few years. I actually had one lecture on differential geometry for control in one of my classes. It was pretty amazing, and definitely very very useful. Not too terribly complex for a first lecture if you have a professor that can explain it well. Anyways, good luck. 


#27
Nov2012, 01:35 AM

P: 59

That actually sounds really cool. I haven't heard much about neural networks yet. Good luck to you too. 


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