Linear Independence: Solving u,v,w Vector Questions

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In summary: Therefore, the given vectors are linearly independent if and only if $a$ is not $0$ and $b$ is not $4$. In summary, the vectors $2u+4v+aw$, $u+2v$, and $2u+bv$ are linearly independent when $a$ is not $0$ and $b$ is not $4$. This is because in order for the homogeneous linear system to have only the trivial solution, the rank of the coefficient matrix must be equal to the number of unknowns, which is satisfied when $a$ is not $0$ and $b$ is not $4$.
  • #1
Yankel
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Hello

I need some help solving the next question:

u,v,w are linearly independent vectors in a vector space V.

the vectors:

2u+4v+aw
u+2v
2u+bv

are linearly independent when:

1. a is not 0
2. b is not 4
3. a is not 0 OR b is not 4
4. a is not 0, and every value of b
5. a is not 0 AND b is not 4

first of all I noticed that answers 1 and 4 are the same.

I also know that x*v+y*u+z*w=0 implies x=y=z=0

but what next ?
 
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  • #2
what do you mean by b not equal to 4, b is a vector no?
 
  • #3
Yankel said:
2u+4v+aw
u+2v
2u+b

According to the possible solutions, the third vector should be $2u+bv$. We have:
$$\lambda_1(2u+4v+aw)+\lambda_2(u+2v)+\lambda_3(2u+bv)=0\Leftrightarrow\\(2\lambda_1+\lambda_2+2 \lambda_3)u+(4\lambda_1+2\lambda_2+b\lambda_3)v+(a\lambda_1)w=0\qquad (1)$$
By hyphothesis, $u,v,w$ are linearly independent so, $(1)$ is satisfied if and only if:
$$\left\{\begin{matrix}2\lambda_1+\lambda_2+2 \lambda_3=0\\4\lambda_1+2\lambda_2+b\lambda_3=0\\a\lambda_1=0\end{matrix}\right.\qquad (2)$$
The homogeneous linear system $(2)$ has only the trivial solution if and only if:
$$\mbox{rank }\begin{bmatrix}{2}&1&{2}\\{4}&{2}&{b}\\{a}&{0}&{0}\end{bmatrix}=3\Leftrightarrow\begin{vmatrix}{2}&1&{2}\\{4}&{2}&{b}\\{a}&{0}&{0}\end{vmatrix}\neq 0\Leftrightarrow a(b-4)\neq 0\Leftrightarrow a\neq 0\wedge b\neq 4$$
The correct answer is 5., $a$ is not $0$ and $b$ is not $4$.
 

FAQ: Linear Independence: Solving u,v,w Vector Questions

1. What does it mean for vectors to be linearly independent?

Linear independence refers to a set of vectors where none of the vectors can be represented as a linear combination of the others. In other words, each vector in the set contributes unique information and cannot be duplicated by a combination of the others.

2. How do you determine if a set of three vectors u, v, and w are linearly independent?

To determine if three vectors are linearly independent, you can set up a system of equations where each vector is represented by its components. If the system has only the trivial solution (all variables equal to 0), then the vectors are linearly independent. If the system has nontrivial solutions, then the vectors are linearly dependent.

3. Can a set of linearly dependent vectors still span a space?

Yes, a set of linearly dependent vectors can still span a space. However, the number of linearly independent vectors in the set will be less than the total number of vectors in the set. This is because the linearly dependent vectors can be removed without changing the span of the space.

4. How do you solve u,v,w vector questions involving linear independence?

To solve u,v,w vector questions involving linear independence, you can use the method of Gaussian elimination to reduce the vectors to echelon form. If the echelon form has a pivot in every column, then the vectors are linearly independent. If there are columns without pivots, then the vectors are linearly dependent.

5. Can a set of linearly independent vectors be orthogonal?

Yes, a set of linearly independent vectors can be orthogonal. In fact, any set of orthogonal vectors is also linearly independent. This is because orthogonal vectors are by definition perpendicular to each other, meaning they cannot be represented as a linear combination of each other.

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