True
When the matrix of coefficients is singular.
A = coefficient matrix (n x n) B = constant matrix (n x 1)
Well, it's important to ask the question first.
Here is a simple way to see it that will help you both understand and remember. Take two equations in two unknowns. You can generalize later. Make a 2x2 matrix using the coefficients only. Now if you multiply this equation by the vector (x,Y) written as a column and placed on the right side of the matrix and you have the 2 equations you started with. Now put the constants, that is to say what each equation is equal to, on the right side of the = sign. If you invert the coefficient matrix on the left, the 2x2 one, and multiply both sides by that inverse, the equation is solved. There is another method known as Cramer's rule that can help you to solve equations using matrices. I suggest you look that one up if you are interested or ask for some more help!
Cut Set matrix provides a compact and effecive means of writing algebriac equations giving branch voltages in terms of tree branches.
Create a matrix of the coefficients of each equation. The solutions to the equations should make up the rightmost column of the matrix. Then, row reduce the matrix until you are able to rewrite the equations and solve them. The matrix should be a 4x5 matrix (4 rows and 5 columns) for four equations with four variables. This is known as a system of equations.
constant matrix
An "inconsistent" set of equations. If they are all linear equations then the matrix of coefficients is singular.
When the matrix of coefficients is singular.
If one (or more) of the equations can be expressed as a linear combination of the others. This is equivalent to the statements the matrix of coefficients does not have an inverse (or is singular), or the determinant of the matrix of coefficients is zero.
A null matrix is a matrix with all its elements zero.EXAMPLES : (0 0) is a null row matrix.(0 0)(0 0) is a null square matrix.NOTE : Text handling limitations prevent the printing of large brackets to enclose the matrix array. Two pairs of smaller brackets have therefore been used.Answer 2:The above answer is a null matrix. However, the nullity of a matrix is the dimension of the kernel. Rank + Nullity = Dimension. So if you have a 4x4 matrix with rank of 2, the nullity must be 2. This nullity is the number of "free variables" you have. A 4x4 matrix is 4 simultaneous equations. If it is rank 2, you have only two independent equations and the other two are dependent. To solve a system of equations, you must have n independent equations for n variables. So the nullity tells you how short you are in terms of equations.
You can solve the system of equations with three variables using the substitute method, or using matrix operations.
matrix
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In simple terms all that it means that there are more solutions than you can count!If the equations are all linear, some possibilities are given below (some are equivalent statements):there are fewer equations than variablesthe matrix of coefficients is singularthe matrix of coefficients cannot be invertedone of the equations is a linear combination of the others
A = coefficient matrix (n x n) B = constant matrix (n x 1)
It depends on your level of expertise. The simplest method is to invert the matrix of coefficients.