Matrix Condition NumberThe condition number for matrix inversion with respect to a matrix norm k¢k of a square matrix A is defined by∙(A)=kAkkA¡1k;
if A is non-singular; and ∙(A)=+1 if A is singular.
The condition number is a measure of stability or sensitivity of a matrix (or the linear system it represents) to numerical operations. In other words, we may not be able to trust the results of computations on an ill-conditioned matrix.
Matrices with condition numbers near 1 are said to be well-conditioned. Matrices with condition numbers much greater than one (such as around 105 for a 5£5Hilbert matrix) are said to be ill-conditioned.
If ∙(A) is the condition number of A , then ∙(A) measures a sort of inverse distance from A to the set of singular matrices, normalized by kAk . Precisely, if A isinvertible, and kB¡Ak
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explain bus incidence matrix.
A matrix that have one or more elements with value zero.
From Wolfram MathWorld: The inverse of a square matrix A, sometimes called a reciprocal matrix, is a matrix A-1 such that AA-1=I where I is the identity matrix.
Tthe matrix multiplication A*Bis defined only if the number of columns in the first matrix, A, is the same as the number of rows in the second, B. Note that the condition for the multiplication of B*A will be the reverse.
They are the number in the matrix.