Understanding Singular Rectangular Matrices

In summary, the conversation discusses the concept of a matrix being singular and how it relates to linear transformations and invertibility. The specific example of rectangular matrices is mentioned, with the discussion centering around the definition of singular and its implications for non-square matrices. The person asking for clarification on the explanation provided in a book.
  • #1
roadworx
21
0
hi,

I have a question on determining whether rectangular matrices are singular.

[tex]\left[1 0 0 1 0\right][/tex]
[tex]\left[1 0 0 0 1\right][/tex]
[tex]\left[0 1 0 1 0\right][/tex]
[tex]\left[0 1 0 0 1\right][/tex]
[tex]\left[0 0 1 1 0\right][/tex]
[tex]\left[0 0 1 0 1\right][/tex]

The book says it's singular. But the explanation isn't very clear. It says something about the first 3 columns treated as vectors give a column of 1's, the final two columns also give a column of 1's. Any better explanation?
 
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  • #2
What do you mean by "singular"? The most general definition I know is that a linear transformation (representable by a matrix) is not invertible. That is, T:U->V is "singular" if there is no linear transformation S:V-> U such that ST(u)= u for all u in U and TS(v)= v for all v in U. If T is represented by an non-rectangular matrix (of dimension "n by m" with n not equal to m), then U and V do not have the same dimension and T is either not "1-to-1" or not "onto". In either case it has no inverse. That is every non-square matrix is "singular".

If you are using a different definition of "singular", please tell us what it is.
 

FAQ: Understanding Singular Rectangular Matrices

1. What is a rectangular matrix?

A rectangular matrix is a type of matrix in linear algebra where the number of rows is not equal to the number of columns. It can also be referred to as a non-square matrix.

2. How is a rectangular matrix represented?

A rectangular matrix is typically represented by its dimensions, with the number of rows listed first followed by the number of columns. For example, a rectangular matrix with 3 rows and 4 columns would be represented as a 3x4 matrix.

3. What is the difference between a rectangular matrix and a square matrix?

A rectangular matrix has a different number of rows and columns, while a square matrix has the same number of rows and columns. This means that a square matrix is always equal in size in both dimensions, while a rectangular matrix can have varying sizes.

4. How is a rectangular matrix multiplied?

To multiply two rectangular matrices, the number of columns in the first matrix must be equal to the number of rows in the second matrix. The product of the multiplication will result in a new rectangular matrix with the number of rows from the first matrix and the number of columns from the second matrix.

5. What are some common applications of rectangular matrices?

Rectangular matrices have various applications in fields such as computer science, statistics, and engineering. They can be used to represent data in spreadsheets, perform transformations in computer graphics, and solve systems of linear equations in engineering problems, among others.

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