Find linear dependence on these vectors

In summary, the task is to find a smaller generating set for a given set of vectors in a vector space <X>, where X = {(1,0,-2,1),(2,-2,0,3),(0,2,-4,-1),(-1,2,-2,-2)}. The solution involves forming a matrix of the vectors and reducing it to echelon form, which results in two equations that can be used to show one vector as a combination of the others. However, the solution does not provide a clear method for reaching this conclusion.
  • #1
ashina14
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Homework Statement


Suppose V = R^4 and let U = <X>, where X = {(1,0,-2,1),(2,-2,0,3),(0,2,-4,-1),(-1,2,-2,-2)}
Find linear dependence on X and use it to find a smaller generating set of U. Repeat the step until you reach a basis for U.


Homework Equations





The Attempt at a Solution



I have formed a matrix of the 4 vectors in X and reduced it to echelon form. I got
(1 | 0 | 2 | 1
0 | 1 | -1 | -1
0 | 0 | 0 | 0
0 | 0 | 0 | 0)

Let's say the 4 vectors were s, t, u, v respectively.
Then xs + xt + yu + zv = 0 is true for some constants w,x,y,z (1)

Then according to the REF form we can form two equations: w = 2y +z and x = -y+z
I thought I could substitute these into equation (1) and end up showing one vector as a combination of the others but I am not able to reach anywhere. Where am I wrong? Is there a better method to go about this?
 
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  • #2
I would have thought that the relationship was implied by the steps to get the echelon form. I.e. in producing the null rows, you effectively executed the equation you're looking for.
 

FAQ: Find linear dependence on these vectors

What is the definition of linear dependence?

Linear dependence is a mathematical concept that describes the relationship between two or more vectors. It means that one vector can be expressed as a linear combination of the other vectors, meaning it can be written as a sum of scalar multiples of the other vectors.

How do you determine if vectors are linearly dependent?

To determine if vectors are linearly dependent, you can use the row reduction method on a matrix formed by the vectors. If a row of zeros is produced, the vectors are linearly dependent. Another method is to calculate the determinant of the matrix formed by the vectors. If the determinant is equal to zero, the vectors are linearly dependent.

Can three vectors be linearly dependent in a three-dimensional space?

Yes, three vectors can be linearly dependent in a three-dimensional space. In a three-dimensional space, three vectors can still be expressed as a linear combination of each other, similar to how two vectors can be linearly dependent in a two-dimensional space.

What are some real-life applications of linear dependence?

Linear dependence has many applications in fields such as physics, engineering, and economics. In physics, linear dependence is used to analyze forces and motion in systems. In engineering, it is used to determine structural stability and to solve problems in circuit analysis. In economics, it is used to study supply and demand and to analyze market trends.

How is linear dependence different from linear independence?

Linear dependence and linear independence are two opposite concepts. Linear dependence means that vectors can be expressed as a linear combination of each other, while linear independence means that they cannot. In other words, linearly dependent vectors are redundant and can be removed, while linearly independent vectors are essential and cannot be removed without changing the system.

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