Specific slope for directional derivative?

In summary, the conversation discusses finding the direction where the rate of change is 18 at the point (-1,2) on the function f(x,y) = (x^2)(y^3)+xy. The speaker suggests using the gradient of the function and a unit direction vector to solve for the unknowns. They also mention the importance of finding the direction, not just the magnitude, of the vector.
  • #1
glog
17
0
Is there a direction where the rate of change is 18, at the point (-1,2) on the function f(x,y) = (x^2)(y^3)+xy?

So I found the gradient of this function, picked a random direction vector u = ( a / (a^2+b^2)^(1/2) , b / (a^2+b^2)^(1/2) ) and took the dot product, and set it to 18... however, I have one equation with two unknowns and no idea how to proceed.

Thank you.
 
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  • #2
glog said:
Is there a direction where the rate of change is 18, at the point (-1,2) on the function f(x,y) = (x^2)(y^3)+xy?

So I found the gradient of this function, picked a random direction vector u = ( a / (a^2+b^2)^(1/2) , b / (a^2+b^2)^(1/2) ) and took the dot product, and set it to 18... however, I have one equation with two unknowns and no idea how to proceed.

Thank you.

don't do that mess..

just say u = <a,b> is unit vector
so, a^2+b^2 = 1 would be your second equation
and
<a,b>.del f = 18 your first equation

I found del f to be <-14,11>
this might be wrong, because I didn't recheck my work
 
  • #3
It doesn't matter if you have 2 unknowns. You're interested in the direction, not the magnitude of the direction vector. Express either a or b in terms of the other and then normalise the vector (a,b)
 

1. What is the specific slope for directional derivative?

The specific slope for directional derivative is a measure of how much a function changes at a given point in a specific direction. It is also known as the directional derivative or the rate of change in a specific direction.

2. How is the specific slope for directional derivative calculated?

The specific slope for directional derivative is calculated using the gradient of the function at the given point and the unit vector in the direction of interest. This can be represented mathematically as the dot product of the gradient and the unit vector.

3. What does the specific slope for directional derivative represent?

The specific slope for directional derivative represents the slope of the tangent line to the function at the given point in the direction of interest. It tells us how much the function is changing in that specific direction.

4. What is the significance of the specific slope for directional derivative?

The specific slope for directional derivative is significant because it allows us to understand how a function is changing in a specific direction. This can be useful in optimization problems or in understanding the behavior of a function in a certain direction.

5. Can the specific slope for directional derivative be negative?

Yes, the specific slope for directional derivative can be negative. This indicates that the function is decreasing in that specific direction. A positive specific slope indicates an increase in the function in the given direction.

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