Recent content by ga14

I'm not really knowledgable about Fourier series yet, is there another way to look at it?

How do you determine if a function is periodic or not without graphing it? For example, cos^2(2pit) is periodic, as is sin^3(2t). But e^(-2t)cos(2pit) is nonperiodic, as is the discrete signal x[n]=cos(2n). Does this have to do with Fourier series somehow? Is there an easier way to determine...

How do you determine if a function is periodic or not without graphing it? For example, cos^2(2pit) is periodic, as is sin^3(2t). But e^(-2t)cos(2pit) is nonperiodic, as is the discrete signal x[n]=cos(2n). Does this have to do with Fourier series somehow? Is there an easier way to determine...

sure sure...you can't do it...admit it ;-) but yes...this was easy and i was dumb for missing 5 points because of it. :o

Hey Guys, Cramming for finals, and here's a problem I got wrong on one of my old exams that's pretty easy, but I just can't do! "A cementite formation reaction follows the the equation: t=Aexp(Q/RT) where t is in secs, Q the activation enegery, R the gas constant (1.98 cal/mol-K), an T is the...

Hey Guys, Cramming for finals, and here's a problem I got wrong on one of my old exams that's pretty easy, but I just can't do! "A reaction follows the equation: t=Aexp(Q/RT) where t is in secs, Q the activation enegery, R the gas constant (1.98 cal/mol-K), an T is the absolute temperature...

I just took the partials with respect to b and m for that equation. Isn't that all you have to do?

In this case m and b are the variables because those are the variables you're trying to optimize. You already know x and y because they give you a set of 10 points, so they are constants.

use partial differentiation and do what? take the partials of that equation with respect to m and b and set them equal to zero?

Hey Guys, I need help with following question: "Suppose you are given a set of ten data points {(x1, y1), (x2,y2), (x3, y3)...(x10,y10)} and you want to find the "best fit" line to the data. In statistics the best fit line (often called the least squares line) is defined to be the line y=mx+b...

Hey Guys, I need help with following question: "Suppose you are given a set of ten data points {(x1, y1), (x2,y2), (x3, y3)...(x10,y10)} and you want to find the "best fit" line to the data. In statistics the best fit line (often called the least squares line) is defined to be the line y=mx+b...

Ok, so I expand out (y_k-(mx_k+b))^2? Then take the partial derivative with respect to x?

^

Hey Guys, I need help with following question: "Suppose you are given a set of ten data points {(x1, y1), (x2,y2), (x3, y3)...(x10,y10)} and you want to find the "best fit" line to the data. In statistics the best fit line (often called the least squares line) is defined to be the line y=mx+b...

Hey Guys, I need help with following question: "Suppose you are given a set of ten data points {(x1, y1), (x2,y2), (x3, y3)...(x10,y10)} and you want to find the "best fit" line to the data. In statistics the best fit line (often called the least squares line) is defined to be the line y=mx+b...