File Name: row space and column space of a matrix .zip
In linear algebra , the column space also called the range or image of a matrix A is the span set of all possible linear combinations of its column vectors. The column space of a matrix is the image or range of the corresponding matrix transformation. The dimension of the column space is called the rank of the matrix and is at most min m , n.
The vector space generated by the rows of a matrix viewed as vectors. The row space of a matrix with real entries is a subspace generated by elements of , hence its dimension is at most equal to. It is equal to the dimension of the column space of as will be shown below , and is called the rank of. The row vectors of are the coefficients of the unknowns in the linear equation system. Hence, the solutions span the orthogonal complement to the row space in , and.
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Let A be an m by n matrix. Since the maximum number of linearly independent rows of A is equal to the rank of A ,. But the maximum number of linearly independent columns is also equal to the rank of the matrix, so. Example 1 : Determine the dimension of, and a basis for, the row space of the matrix.
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