How do you calculate f'(a) in terms of the blue values?

In summary, the conversation discusses the concept of taking a derivative of a function in terms of vectors, specifically using the limit definition of the derivative that was learned in Calculus 1. The conversation also includes an example of how to calculate d/dt (f(a+tu)) |t=0 and confirms that it is equal to f'(a).
  • #1
kingwinner
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0
1) http://www.geocities.com/asdfasdf23135/advcal7.JPG

Now I don't understand why the stuff in blue are equal (completely lost...), can someone please explain why?

Thanks!
 
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  • #2
It's a definition! They are equal because they are defined that way! (That is, of course, just the ordinary definition of derivative put in terms of vectors.
 
  • #3
But how can you simplify d/dt (f(a+tu)) |t=0 to get
lim [f(a+tu)-f(a)] / t ?
t->0


I don't understand how I can calculate d/dt (f(a+tu)) |t=0, what is this equal to in terms of limits and how can I get there?
 
  • #4
Hm, let me try to explain...

You can tell that the expression on the left is essentially just the limit definition of the derivative that you learned in Calc 1, except for the fact that now it's a function that takes a vector that we're taking the derivative of. The derivative is being evaluated at the point a and in the direction of the vector u. The parameter t let's you "walk" a little bit away from a in the direction of u on the function (analogous to making a step [itex]\Delta x[/itex] for a single-variable function).

Then, the right hand side is just writing this same concept in a different form. It takes the derivative of the function f along our "walk" (with respect to the parameter t). Then, where do we want to find the derivative? At the location a, of course! So we have to evaluate our derivative df/dt when t=0 (when we're still at a).

In terms of actually calculating something, can't you just substitute a+tu into the function and take the derivative with respect to t?

Example:
[tex]\vec{f}(x,y) = x \hat{i} + y^2 \hat{j}[/tex]

Let [tex]\vec{a} = \langle a_1, a_2 \rangle = \langle 1, 1 \rangle[/tex], [tex]\vec{u} = \langle u_1, u_2 \rangle = \langle -1, 2 \rangle[/tex]

Then
[tex]\vec{f}(\vec{a} + t\vec{u}) = \vec{f}(a_1 + t u_1, a_2 + t u_2) = \vec{f}(1-t, 1+2t) = (1-t) \hat{i} + (1+2t)^2 \hat{j}[/tex]

[tex]\frac{d\vec{f}(\vec{a} + t\vec{u})}{dt} \bigg|_{t=0} = -1 \hat{i} + 2 (1+2t)^2 \hat{j} \bigg|_{t=0} = -\hat{i} + 2\hat{j}[/tex]

Can someone confirm this is correct? It's been a while since I've done this. The notation may not be spot on either.
 
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  • #5
"...the expression on the left is essentially just the limit definition of the derivative that you learned in Calc 1..."

But what I've learned in calculus 1 is that,
f '(a)= lim [f(a+h) - f(a)] / h
h->0

So shouldn't
lim [f(a+tu)-f(a)] / t be equal to f '(a), instead of d/dt (f(a+tu)) |t=0?
t->0
 
  • #6
?? d/dt (f(a+ tu))|t=0 IS f '(a)!
 
  • #7
HallsofIvy said:
?? d/dt (f(a+ tu))|t=0 IS f '(a)!

Why? For d/dt (f(a+ tu))|t=0, shouldn't you calculate the derivative FIRST and then evaluate at t=0?
 
  • #8
Yes, which is exactly what f'(a) means! If that isn't how you would calculate f'(a) then how would you?
 

FAQ: How do you calculate f'(a) in terms of the blue values?

What is a direction derivative?

A direction derivative is a measure of the rate of change of a function in a specific direction. It tells us how the function changes as we move in a particular direction from a given point.

How is a direction derivative calculated?

A direction derivative is calculated by taking the dot product of the gradient of the function at a specific point and a unit vector in the direction you want to measure the rate of change.

What is the difference between a direction derivative and a partial derivative?

A direction derivative measures the rate of change of a function in a specific direction, while a partial derivative measures the rate of change of a function with respect to one variable, holding all other variables constant.

When is a direction derivative used?

A direction derivative is used in multivariate calculus to find the direction of steepest ascent or descent of a function at a given point. It is also used in optimization problems to find the maximum or minimum value of a function in a specific direction.

Can a direction derivative be negative?

Yes, a direction derivative can be negative if the function is decreasing in the specified direction. It can also be zero if the function is constant in that direction, and positive if the function is increasing in that direction.

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