Prove a theorem about a vector space and convex sets

In summary, if the set X of vectors {x1,...,xn} in the vector space E is convex, then all convex combinations of X also belong to X. This can be proven by using induction and considering the convexity of the set. For example, for n=2, it is easy to see that the convex combination of two vectors must lie on the line between them. For n=3, it can be visualized as a triangle and a picture can aid in understanding the proof.
  • #1
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Summary:: Be the set X of vectors {x1,...,xn} belong to the vector space E. If this set X is convex, prove that all the convex combination of X yet belong to X. Where convex combination are the expression t1*x1 + t2*x2 + ... + tn*xn where t1,...,tn >= 0 and t1 + ... + tn = 1

I tried to suppose xn > xn-1 > ... > x1, so in this way we have two limits, and the convex requires that all elements of E [v1,vn] belongs to X.
Now here i smell a rat: I suppose that xn > t1*x1 + t2*x2 + ... + tn*xn > x1, in such way that it will automatically belongs to E. The problem is how to prove my statement...

[Moderator's note: Moved from a technical forum and thus no template.]
 
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  • #2
xn > t1*x1 + t2*x2 + ... + tn*xn > x1

Remember these are vectors, you don't have a natural way to compare them. Convexity of E only says this sum is in E if it happens to lie on the line between x1 and xn, which is very unlikely for random coefficients.

I would suggest trying to do induction. n=2 is as easy as you think. What about n=3? This is just a triangle, so a picture might help you think about it.
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of objects called vectors, which can be added together and multiplied by numbers called scalars. It is a fundamental concept in linear algebra and is used to model physical quantities that have both magnitude and direction.

2. How is a theorem about a vector space proven?

A theorem about a vector space is proven using deductive reasoning and logical arguments. This involves starting with a set of axioms or assumptions, and then using mathematical techniques such as algebra and geometry to arrive at a conclusion that is true for all possible cases.

3. What is a convex set?

A convex set is a subset of a vector space that contains all the points on a line segment connecting any two of its points. In other words, if you take any two points within a convex set, the line segment connecting them will also be contained within the set. This property is important in optimization and geometry.

4. How does a theorem about a vector space relate to convex sets?

Theorem about a vector space and convex sets are closely related because convex sets are a special type of subset of a vector space. Many theorems about vector spaces can be applied to convex sets, and vice versa. For example, the Hahn-Banach theorem, which states that every convex set can be separated from a point outside of it by a hyperplane, has important implications for both vector spaces and convex sets.

5. What are some real-world applications of theorems about vector spaces and convex sets?

Theorems about vector spaces and convex sets have a wide range of applications in fields such as engineering, economics, computer science, and physics. For example, they are used in optimization problems to find the most efficient solutions, in computer graphics to create 3D models, and in game theory to analyze strategic decisions. They also have applications in machine learning, control systems, and signal processing.

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