Author Archives: Carolyn Johnston
Controlling Type I Experimental Error
Full disclosure: I’m currently taking a high-speed graduate class in Experimental Design from the Colorado State University statistics department. Right now, we’re working on methods for controlling Type I errors (“false alarms”) in cases where you might want to do … Continue reading
How I think about the neural network backpropagation algorithm
My husband Bernie says that every mathematician has a favorite mathematical object, and if that is so, then my favorite mathematical objects are matrices. I try to chunk all my mathematical understandings into matrix expressions, essentially translating everything into my … Continue reading
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Mathematical Derivation of the Extended Kalman Filter
This writeup is an extension of the writeup I posted last week, Mathematical Derivation of the Bayes and Kalman Filters. Both these writeups were written when I was studying Probabilistic Robotics by Sebastian Thrun, Wolfram Burgard, and Dieter Fox; I think that … Continue reading
Mathematical Derivation of the Bayes and Kalman filters
I read a lot of technical documents, but sometimes I just don’t get them without a lot of extra work. In particular, I’m prone to getting stuck on mathematical conclusions that I don’t follow (usually because there is a step … Continue reading
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