Linear dependence of polynomical functions

In summary, the concept of linear independence and the role of the Wronskian in determining it were discussed in the conversation. It was noted that the Wronskian is only used to show linear independence and if it equals 0, it does not necessarily mean the vectors are dependent. The example of a set of functions in the vector space $\mathbb{R}_2[x]$ was given, and it was concluded that the functions are linearly dependent.
  • #1
Fernando Revilla
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I quote a question from Yahoo! Answers

Trying to understand the material here. It says that "...the set of solutions is linearly independent on I if and only if W(y1, y2...yn) doesn't = 0 for every x in the interval. (W(y1, y2...yn) being the Wronskian.)

But then I read a comment on youtube: "your first example is wrong, the wronsky is only used to show linear independence. if your determinant is 0 , it doesn't always mean ur your vectors are linear dependent." I guess the wronskian was used for vectors here but I imagine the concept is same for DE's?

So I have this set of functions f1(x) = x, f2(x) = x^2, f3(x) = 4x - 3x^2

and I get the wronskian to = 0. So by the youtuber's comment does this mean these set of functions could either be linearly independent or dependent? How do you determine whether they're independent or dependent?

I have given a link to the topic there so the OP can see my response.
 
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  • #2
How do you determine whether they're independent or dependent?

Consider the vector space $\mathbb{R}_2[x]$ (polynomical functions with degree $\le 2$) and the canonical basis $B=\{1,x,x^2\}$. The respective coordinates are: $$[x]_B=(0,1,0)\;,\;[x^2]_B=(0,0,1)\;,\;[ 4x - 3x^2]_B=(0,4,-3)$$ But $\mbox{rank } \begin{bmatrix} 0 & 1 &\;\; 0\\ 0 & 0 & \;\;1 \\ 0 & 4 &-3\end{bmatrix}=2.$ We have no maximum rank, so the rows are linearly dependent. Using the standard isomorphism between vectors and coordinates, we conclude that $f_1(x)=x$, $f_2(x)=x^2$ and $f_3(x)=4x - 3x^2$ are linearly dependent.
 

1. What is linear dependence of polynomial functions?

Linear dependence of polynomial functions refers to the relationship between two or more polynomial functions, where one function can be expressed as a linear combination of the other functions. In other words, one function can be written as a sum of multiples of the other functions.

2. How can you determine if polynomial functions are linearly dependent?

To determine if polynomial functions are linearly dependent, you can use the method of finding the determinant of the matrix formed by the coefficients of the functions. If the determinant is equal to zero, then the functions are linearly dependent. If the determinant is not equal to zero, then the functions are linearly independent.

3. What is the significance of linear dependence in polynomial functions?

Linear dependence in polynomial functions is significant because it allows us to simplify the functions and reduce the number of independent variables. This can make it easier to solve equations and understand the overall behavior of the functions.

4. Can polynomial functions with different degrees be linearly dependent?

Yes, polynomial functions with different degrees can still be linearly dependent. For example, a quadratic function and a linear function can be linearly dependent if the coefficients of the linear function are multiples of the coefficients of the quadratic function.

5. How is linear dependence related to the concept of span?

The concept of span refers to the set of all possible linear combinations of a given set of vectors. In polynomial functions, linear dependence is related to the span of the functions because if the functions are linearly dependent, then the span of the functions will be a smaller subset of the total possible combinations of the functions.

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