Real Analysis - Differentiation in R^n - Example of a specific function

In summary, the conversation discusses the task of finding a continuous function with partial derivatives at (0,0) where the vector of these derivatives does not point in the direction of maximal change. The conversation mentions a theorem in multivariate calculus and suggests looking at its conditions and proof to construct the desired function. The use of the term "counterexample" and the omission of the word "gradient" may provide further clues.
  • #1
GridironCPJ
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0

Homework Statement



Give an example of a continuous function f:R^2→R having partial derivatives at (0,0) with
f_1 (0,0)≠0,f_2 (0,0)≠0
But the vector (f_1 (0,0),f_2 (0,0)) does not point in the direction of maximal change, even though there is such a direction.

(If this is too difficult to read, please see the PDF for a nicer version)

Note that this is a problem from TBB's Elementary Real Analysis

Homework Equations



none

The Attempt at a Solution



I have no idea how to attempt the construction of such a function. Any tips, suggestions, or a walkthrough of how to find such a function would be greatly appreciated. If you feel like giving me an answer, please explain it because understanding this is the most important part of this.
 

Attachments

  • TBB Problem 12.4.18.pdf
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  • #2
I think you've recognized that this problem has you finding a "counterexample" to a well-known theorem in multivariate calc (it's not really a counterexample to the the theorem, because the theorem is true). If I were you, I would look carefully at the statement and proof of that theorem to see what conditions a function needs to satisfy in order for the theorem to apply. Then try to construct a function that doesn't have the necessary qualities.

Also, the fact that the problem doesn't use the word "gradient" may be a hint.
 

Related to Real Analysis - Differentiation in R^n - Example of a specific function

What is real analysis?

Real analysis is a branch of mathematics that deals with the study of real numbers and their properties. It includes topics such as limits, continuity, differentiation, integration, and sequences.

What is differentiation in R^n?

Differentiation in R^n refers to the process of finding the rate of change or slope of a function in n-dimensional space. It is an extension of the concept of differentiation in one-dimensional space and involves partial derivatives.

Can you give an example of a specific function for differentiation in R^n?

One example of a function for differentiation in R^n is a multivariate polynomial, such as f(x,y) = x^2 + y^3. To find the partial derivative with respect to x, we treat y as a constant and differentiate the function as we would in one-dimensional space. The result would be f'(x,y) = 2x. Similarly, the partial derivative with respect to y would be f'(x,y) = 3y^2.

Why is differentiation in R^n important?

Differentiation in R^n is important because it allows us to analyze functions in multiple dimensions, which is crucial in many real-world applications. It helps us understand the behavior of functions and their rates of change in various directions.

What are some practical applications of differentiation in R^n?

Some examples of practical applications of differentiation in R^n include optimization problems in economics and physics, curve fitting in statistics, and gradient descent algorithms in machine learning. It is also used in engineering, finance, and other fields to model and analyze complex systems.

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