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hkus10
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1) Let A be an n x n matrix. Prove that if Ax= 0 for all n x 1matrices, then A=O.
Can you show me the steps of solving this problem?
Please!
Can you show me the steps of solving this problem?
Please!
Show us what you've tried. The rules of this forum say that we aren't supposed to provide any help if you haven't given the problem a try.hkus10 said:1) Let A be an n x n matrix. Prove that if Ax= 0 for all n x 1matrices, then A=O.
Can you show me the steps of solving this problem?
Please!
Mark44 said:Show us what you've tried. The rules of this forum say that we aren't supposed to provide any help if you haven't given the problem a try.
A linear equation is an algebraic equation in which each term is either a constant or the product of a constant and a single variable. The highest power of the variable in a linear equation is always 1.
To solve a system of linear equations, you can use various methods such as substitution, elimination, or graphing. In substitution, you solve for one variable in one equation and substitute the value into the other equation. In elimination, you add or subtract the equations to eliminate one variable. In graphing, you plot the equations on a graph and find the point of intersection.
A matrix is a rectangular array of numbers, variables, or expressions arranged in rows and columns. It is commonly used to represent systems of linear equations, perform matrix operations, and solve systems of equations using matrices.
To multiply matrices, the number of columns in the first matrix must be equal to the number of rows in the second matrix. The product matrix will have the same number of rows as the first matrix and the same number of columns as the second matrix. To find the value in each cell of the product matrix, you multiply the corresponding elements in the rows and columns of the matrices and add the products.
The inverse of a matrix is a matrix that, when multiplied by the original matrix, results in the identity matrix. The inverse of a matrix can be found by using various methods such as Gaussian elimination, adjoint method, or inverse matrix formula.