00:01
We'll ask to, let's see here, minimize this function here.
00:08
X minus 2 squared plus y squared are subject to the constraint that y minus x, y minus squared for x equals 0.
00:15
So here's our constraint.
00:18
So we form our augmented function here, x minus 2 square plus y squared plus lambda times our constraint times c here.
00:28
We take partial derivatives, respect to x, y, and lambda, and set them all equal to 0.
00:34
And so with respect to x, we get 2x minus 4, minus lambda over squared of x.
00:40
For y, we get lambda plus 2y equals 0.
00:43
And when we expect a lambda, we just get c, and that equals 0, which we, you know, that basically just gives us our constraint equation back...