Working on lipschitz function and contraction map

In summary, we can use the given conditions to show that the 2-norm of the difference between two points in R^2 is bounded by a constant multiple of the 2-norm of the distance between those points.
  • #1
simo1
29
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if you given a function f from R^2 to R^2 f(x)=<f_1(x),f_2(x)>, x in R^2

with f_1 and f_2 from R^2 to R being differentiable on R. if there is contants K_1 and K_2 greater than or equal to 0 so the 2-norm of (gradient f_1(x)) is less than or equal to K_1 and 2-norm of (gradient f_2(x)) is less than or equal to K_2 for x in R^2.
show that the 2-norm of (f(x)-f(y)) is less than or equal to [square root of (k_1^2 -k_2^2)] multipy by 2-norm of (x-y) for all x and y in R^2

can i get hints on how to start
 
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  • #2
simo said:
if you given a function f from R^2 to R^2 f(x)=<f_1(x),f_2(x)>, x in R^2

with f_1 and f_2 from R^2 to R being differentiable on R. if there is contants K_1 and K_2 greater than or equal to 0 so the 2-norm of (gradient f_1(x)) is less than or equal to K_1 and 2-norm of (gradient f_2(x)) is less than or equal to K_2 for x in R^2.
show that the 2-norm of (f(x)-f(y)) is less than or equal to [square root of (k_1^2 k_2^2)] multipy by 2-norm of (x-y) for all x and y in R^2 (That – should be a +.)

can i get hints on how to start
Hi simo, and welcome to MHB! By the definition of the 2-norm, $\|f(x) - f(y)\|_2^2 = |f_1(x) - f_1(y)|^2 + |f_2(x) - f_2(y)|^2.$ Now use the result from http://mathhelpboards.com/analysis-50/converging-maps-9673.html (applied to the functions $f_1$ and $f_2$) to deduce that $\|f(x) - f(y)\|_2^2 \leqslant (K_1^2 + K_2^2)\|x-y\|^2.$ Then take the square root of both sides.
 

Related to Working on lipschitz function and contraction map

1. What is a Lipschitz function?

A Lipschitz function is a type of mathematical function that satisfies the Lipschitz condition, which requires the function to have a finite slope and be locally bounded. This means that the rate of change of the function is limited, preventing it from becoming too steep or rapidly changing.

2. Why is it important to work on Lipschitz functions?

Lipschitz functions are important in many areas of mathematics, particularly in the study of differential equations and optimization problems. They also have applications in computer science and engineering, where they are used to ensure stability and convergence in algorithms and models.

3. What is a contraction map?

A contraction map is a type of function that satisfies the contraction property, which requires the distance between the images of any two points in the function's domain to be smaller than the distance between the two original points. This means that the function "contracts" the space, bringing points closer together as they are mapped.

4. How are Lipschitz functions and contraction maps related?

Lipschitz functions and contraction maps are closely related as a Lipschitz function is also a contraction map. This is because the Lipschitz condition ensures that the function is contracting, meaning that it decreases the distance between points in its domain. This property is useful in proving the existence and uniqueness of solutions in differential equations and optimization problems.

5. What are some common techniques for working on Lipschitz functions and contraction maps?

Some common techniques for working on Lipschitz functions and contraction maps include using the Mean Value Theorem, the Banach Fixed Point Theorem, and various inequalities such as the Cauchy-Schwarz inequality. Other techniques may involve using geometric properties and transformations to simplify the functions and prove their properties.

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