Solving Grad f and Grad g for Math Problem

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In summary, the conversation discusses problems involving the function f(x, y)=xye^(− ((x−a)^2)− ((y−b)^ 2)). The participants solve for the direction that will increase the function values the quickest from the point (a, b), find an equation for the tangent plane at the point (a, b, ab), and calculate a close value to f(9a/10, 6b/5). They also determine the points where the tangent plane is horizontal. There are some errors in the derivatives provided, and they must be corrected to get the correct answers.
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electricman
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Hi,

I have some problems to solve this:

a=8 , b=5

Let f (x, y)=xye^(− ((x−a)^2)− ((y−b)^ 2)). In which direction, one will go from the point (a, b) in the definition amount if one wants to that the function values will increase so quickly as possible? Decide an equation for tangent plane to the surface z=f (x, y) in the point (a, b, ab). Use differential to f in order to calculate a close value to f (9a/10, 6b/5). In which points, key planet is to the surface z=f (x, y) horizontal?

I derivated and got:

df/dx = ye^(− ((x−a)^2)− ((y−b)^ 2)) * (-2x+2a) + ye^(− ((x−a)^2)− ((y−b)^ 2))

df/dy = xe^(− ((x−a)^2)− ((y−b)^ 2)) * (-2y+2a) + ye^(− ((x−a)^2)− ((y−b)^ 2))

and grad f(a,b) = (y,x) = (5,8) , Is this correct?
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And for the tangent plane:

g(x,y,z)=f(x,y) - z

grad g = (5,8,-1)

And the tangent plane: 5(x-8)+8(y-5)+(1)(z-40)=0 => 5x+8y-z=40 , Is this correct?

_____________________________________________________________

And for the close value:

z=5x+8y-40 close to (8,5). In (7.2,6) is z=5*7,2+8*6-40=44 , Is this correct?

_________________________________________________________

The are horizontal when df/dx = df/dy = 0 , Is this correct? I don't know if i can get a value to this?
 
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  • #2
electricman said:
df/dx = ye^(− ((x−a)^2)− ((y−b)^ 2)) * (-2x+2a) + ye^(− ((x−a)^2)− ((y−b)^ 2))

(I presume you mean [tex]\frac{\partial}{\partial x}[/tex].)

There should be an 'x' in the first term.

[tex]\frac{\partial f}{\partial x} = [/tex] xye^(− ((x−a)^2)− ((y−b)^ 2)) * (-2x+2a) + ye^(− ((x−a)^2)− ((y−b)^ 2)).

The same missing 'y' in [tex]\frac{\partial f}{\partial y}[/tex].

Correct these first, in order to get the correct answers for the rest of the problems.
 

FAQ: Solving Grad f and Grad g for Math Problem

What is the purpose of solving Grad f and Grad g for a math problem?

The purpose of solving Grad f and Grad g for a math problem is to find the gradient of a function at a given point and the direction of steepest ascent or descent of the function at that point. This information can be used to optimize a function or solve optimization problems.

What is the difference between Grad f and Grad g?

Grad f and Grad g are both gradients, which represent the rate of change of a function. The main difference between them is that Grad f represents the gradient of one function, while Grad g represents the gradient of a different function. They can be calculated separately and used to solve different problems.

What are the steps to solve Grad f and Grad g for a math problem?

The following are the general steps to solve Grad f and Grad g for a math problem:1. Calculate the partial derivatives of the functions f and g with respect to each variable.2. Plug in the values of the given point into the partial derivatives to find the values of Grad f and Grad g.3. Compare the values of Grad f and Grad g to determine the direction of steepest ascent or descent.4. Use this information to optimize the function or solve optimization problems.

What are some real-life applications of solving Grad f and Grad g for a math problem?

Solving Grad f and Grad g can be used in various fields such as economics, physics, engineering, and computer science. Some real-life applications include optimizing production processes, finding the most efficient route for transportation, and designing computer algorithms for machine learning and artificial intelligence.

What are some common challenges when solving Grad f and Grad g for a math problem?

Some common challenges when solving Grad f and Grad g include:- Ensuring that the partial derivatives are calculated correctly.- Identifying the correct values to plug into the partial derivatives.- Interpreting the results and determining the correct direction of steepest ascent or descent.- Applying the information to optimize the function or solve the optimization problem correctly.

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