Can the Subdifferential of a Non-Convex Function at a Point be Computed?

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In summary, the conversation discussed the definition of f:R->R, which is a function defined differently for x=0 and x!=0. The topic of subdifferentiation was brought up and the OP expressed confusion on how to approach finding the subderivative at 0. The conversation also referenced Wikipedia's definition of subderivative and discussed the example of a convex function. However, it was noted that the function in question is not convex, making it difficult to find the subderivative. The OP mentioned graphing the function and observing a slope of 0 on both sides of 0, but was unsure if this was the correct approach.
  • #1
braindead101
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Define f:R->R by
f(x) = { x^2 sin(1/x) x!=0, 0 x=0
Compute subdifferential f(0)

I went through my notes on subdifferentiation and still do not have a clue how to do this process, is there a formula to directly do this? any help would be greatly appreciated.
 
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On the entire of the world wide web, the first result on "subdifferentiation" comes from this thread. What exactly is subdifferentiation?
 
  • #3
Wikipedia says: http://en.wikipedia.org/wiki/Subderivative

(I know what people are going to say; don't link to wiki; but there doesn't really seem to be another website on this this is openly accessible!)
 
  • #4
Ok with that definition:

What makes you (the OP) think that we can find the subderiavative at zero? Is the function convex...
 
  • #5
the function is not convex. but it is an assignment question so it must be doable some how.
so i looked at the wiki you sent me and saw the example. but then i guess it is not the same
as my question as that function is convex and mine is not.
Example i am referring to:
Consider the function f(x)=|x| which is convex. Then, the subdifferential at the origin is the interval [−1, 1].

But with that said, I graphed the x^2sin(1/x) function to try to see the behaviour around 0, and both sides are approaching 0 and the slope seems to be also 0.. but i don't know if this is how to actually do it.

what are your thoughts after that wiki read?
 

What is subdifferentiation at a point?

Subdifferentiation at a point is the process of finding the subgradient of a function at a specific point. It is used to determine the slope or rate of change of a function at a certain point.

How is subdifferentiation different from differentiation?

Subdifferentiation is similar to differentiation in that it also involves finding the slope of a function. However, while differentiation calculates the slope at a single point, subdifferentiation calculates the slope over a range of points.

What is the purpose of subdifferentiation?

The main purpose of subdifferentiation is to find the minimum or maximum value of a function over a range of points. It is commonly used in optimization problems to find the best solution for a given set of constraints.

What is the relationship between subdifferentiation and convexity?

Subdifferentiation is closely related to convexity in that it is used to determine whether a function is convex or not. If the subgradient of a function is always increasing, then the function is said to be convex.

What are some real-life applications of subdifferentiation?

Subdifferentiation has many practical applications, such as in economics, engineering, and finance. It is used to solve optimization problems in supply and demand analysis, determine the optimal design of a structure, and minimize risk in investment portfolios, among others.

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