How can I prove that f + g is convex?

In summary, the conversation discusses the concept of convex functions and how the sum of two convex functions is also convex. The definition of a convex function is provided and the conversation delves into the conditions for a function to be considered convex. There is also a discussion on how to prove that the sum of two convex functions is convex using algebraic methods.
  • #1
mohdhm
42
0
hey everyone:

Use a definition to work forward from each of the following statements.

b. for functions f anf g the function f + g is convex, where f + g is the function whoes value at any point x is f(x) + g(x).

Definition of a convex function: http://en.wikipedia.org/wiki/Convex_function (the equation)

So guys, I'm really stumped, what are we asked to do here. I have a hunch that we have to add g(x) of a convex function to the f(x) of one, but we only have the function of f to work with, and also in the definition we get a y variable, that was not even mentioned in the question... what is up with that. If someone can at least guide me in the right direction, i'd be eternally grateful
 
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  • #2
No wonder you are stumped! The "theorem" as you state it is false. Did you not include the condition that f(x) and g(x) are convex themselves?

I have absolutely no idea what you mean by "g(x) of a convex function"- either g(x) itself is a convex function or it is not, but there is no "g(x) of a convex function".

A function is convex if and only if, for x and y any two points in its domain, [itex]tf(x)+ (1-t)f(y)\ge f(tx+ (1-t)y)[/itex]. In other words, the straight line between (x,f(x)) and (y, f(y)) is above the point on the graph (tx+ (1-t)y, f(tx+ (1-t)y)).

Okay, if the function is f(x)+ g(y) that means you want to prove that
[tex]t(f(x)+ g(x))+ (1-t)(f(y)+ g(y))\ge f(tx+ (1-t)y)+ g(tx+ (1-t)y[/tex]
and you can assume that is true of f(x) and g(x) separately. Looks like straightforward algebra to me.
 

1. What is a convex function?

A convex function is a mathematical function that satisfies a specific property known as convexity. This means that any line segment connecting two points on the graph of the function lies above or on the graph itself. In other words, the function is always curving upwards and never has any dips or concave portions.

2. Why are convex functions important in mathematics?

Convex functions have many important applications in mathematics, particularly in optimization and economics. They have desirable properties that make them easier to work with, such as being differentiable and having a unique minimum point. They are also useful in proving the convergence of algorithms and in game theory.

3. How do you prove that a function is convex?

To prove that a function is convex, you need to show that it satisfies the definition of convexity. This can be done by taking any two points on the graph of the function and showing that the line segment connecting them lies above or on the graph. Alternatively, you can use the second derivative test to show that the function has a positive or zero second derivative, which is a necessary and sufficient condition for convexity.

4. Can a function be both convex and concave?

No, a function cannot be both convex and concave. These are two opposite properties, where a convex function always curves upwards and a concave function always curves downwards. However, a function can have both convex and concave portions, but it cannot have both properties at the same time.

5. What is the importance of convex functions in optimization?

Convex functions are essential in optimization because they have a unique minimum point, which is also the global minimum. This means that the minimum value of the function is the best possible solution to the optimization problem. Convex functions are also easier to optimize, as there are many efficient algorithms that can be used to find the minimum point. In addition, convex functions have many desirable properties, such as being continuous and having a finite and non-empty domain, which make them suitable for use in real-world applications.

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