Vector equation vs Matrix equation

In summary, the vector equation has scalar-vector multiplication, while the matrix equation has matrix-vector multiplication. This is because a matrix can be thought of as a vector of vectors, making the order of multiplication important. Switching the order would result in an undefined product.
  • #1
Instinctlol
79
0
I am a little bit confused about these 2.
A vector equation goes like this: x1v1+x2v2+...+xnvn=b
and Matrix equation goes like this:
Ax= [v1 v2 .. vn][x1
x2
.
.
.
xn]

v is a vector in the vector equation, but in the matrix equation x becomes the vector and v is just the matrix.

My question is, why does it get switched like this?
 
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  • #2
Instinctlol said:
I am a little bit confused about these 2.
A vector equation goes like this: x1v1+x2v2+...+xnvn=b
and Matrix equation goes like this:
Ax= [v1 v2 .. vn][x1
x2
.
.
.
xn]

v is a vector in the vector equation, but in the matrix equation x becomes the vector and v is just the matrix.

My question is, why does it get switched like this?

There are different kinds of multiplication going on. In your first equation, each term is a scalar times a vector (I'm assuming that the xi's are scalars).

Your second equation is the product of what appears to be an n X n matrix and a vector with n components. If you switched the order in the 2nd equation to xA, the multiplication would not be defined.
 
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Likes momina
  • #3
in your "vector equation" the v's are vectors, and the x's are field elements (scalars).

one way of thinking of a matrix is "a vector of vectors" (it's a 2-array, not a 1-array). so in your "matrix equation" each v is a column (which is why matrix entries need TWO subscripts, one for the row, and one for the column). so what you really have is:

[tex]\begin{bmatrix}v_{11}&v_{12}&\dots&v_{1n}\\v_{21}&v_{22}&\dots&v_{2n}\\ \vdots&\vdots&\ddots&\vdots\\v_{m1}&v_{m2}&\dots&v_{mn}\end{bmatrix} \begin{bmatrix}x_1\\x_2\\ \vdots\\x_n\end{bmatrix} = \begin{bmatrix}v_{11}x_1 + v_{12}x_2 + \dots + v_{1n}x_n\\v_{21}x_1 + v_{22}x_2 + \dots + v_{2n}x_n\\ \vdots\\v_{m1}x_1 + v_{m2}x_2 + \dots + v_{mn}x_n\end{bmatrix} = \begin{bmatrix}b_1\\b_2\\ \vdots\\b_n\end{bmatrix}[/tex]

writing Ax = b is just an abbreviation for that god-awful mess above.
 

What is the difference between a vector equation and a matrix equation?

A vector equation is a mathematical expression that represents a vector in terms of its components. It is typically written in the form of a = b, where a is the vector and b is a combination of scalar quantities and other vectors. On the other hand, a matrix equation is an expression that represents a system of linear equations using matrices. It is typically written in the form of Ax = b, where A is a matrix, x is a vector of variables, and b is a vector of constants. Essentially, the main difference between the two is that a vector equation represents a single vector, while a matrix equation represents a system of vectors.

Can a vector equation be converted into a matrix equation?

Yes, a vector equation can be converted into a matrix equation by representing the vector as a column matrix and the scalar quantities as a row matrix. For example, the vector equation a = b can be written as the matrix equation Ax = b, where A is a 1x1 matrix representing a and x is a 1x1 matrix representing b.

Which is more commonly used in mathematical applications, vector equations or matrix equations?

This depends on the specific application. In general, vector equations are used for representing single vectors or transformations in a single direction, while matrix equations are used for representing systems of vectors or transformations in multiple directions. Both are commonly used in various fields such as physics, engineering, and computer science.

Can a vector equation be solved using matrix operations?

Yes, a vector equation can be solved using matrix operations. In fact, converting a vector equation into a matrix equation allows us to use matrix operations such as addition, subtraction, multiplication, and inversion to solve the equation. This is especially useful for solving systems of linear equations, where the use of matrices greatly simplifies the process.

Are there any limitations to using vector equations or matrix equations?

Both vector equations and matrix equations have their own limitations. For example, vector equations may not be able to accurately represent complex systems of vectors, while matrix equations may not be able to accurately represent nonlinear systems. It is important to choose the appropriate type of equation based on the specific problem at hand.

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