Search results
Results from the WOW.Com Content Network
Let A be an m × n matrix and k an integer with 0 < k ≤ m, and k ≤ n.A k × k minor of A, also called minor determinant of order k of A or, if m = n, the (n − k) th minor determinant of A (the word "determinant" is often omitted, and the word "degree" is sometimes used instead of "order") is the determinant of a k × k matrix obtained from A by deleting m − k rows and n − k columns.
The program structure of this algorithm is a simple triple-loop, as in the standard Gaussian elimination. However in this case the matrix is modified so that each M k,k entry contains the leading principal minor [M] k,k. Algorithm correctness is easily shown by induction on k. [4]
For example, a 2,1 represents the element at the second row and first column of the matrix. In mathematics, a matrix (pl.: matrices) is a rectangular array or table of numbers, symbols, or expressions, with elements or entries arranged in rows and columns, which is used to represent a mathematical object or property of such an object.
In the mathematical discipline of linear algebra, a matrix decomposition or matrix factorization is a factorization of a matrix into a product of matrices. There are many different matrix decompositions; each finds use among a particular class of problems.
The Hessian matrix plays an important role in Morse theory and catastrophe theory, because its kernel and eigenvalues allow classification of the critical points. [2] [3] [4] The determinant of the Hessian matrix, when evaluated at a critical point of a function, is equal to the Gaussian curvature of the function considered as a manifold. The ...
If is a singular matrix of rank , then it admits an LU factorization if the first leading principal minors are nonzero, although the converse is not true. [ 9 ] If a square, invertible matrix has an LDU (factorization with all diagonal entries of L and U equal to 1), then the factorization is unique. [ 8 ]
In particular, the diagonal entries are the principal minors of , which of course are also principal minors of , and are thus non-negative. Since the trace of a matrix is the sum of the diagonal entries, it follows that tr ( ⋀ j M k ) ≥ 0. {\displaystyle \operatorname {tr} \left(\textstyle \bigwedge ^{j}M_{k}\right)\geq 0.}
Compute the Sylvester matrix associated to and (). Rearrange each row in such a way that an odd row and the following one have the same number of leading zeros. Compute each principal minor of that matrix. If at least one of the minors is negative (or zero), then the polynomial f is not stable.