The eigen values of a matirx are the values L such that Ax = Lx
where A is a matrix, x is a vector, and L is a constant.
The vector x is known as the eigenvector.
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First, a small note: an m-by-n or m x n matrix has m rows and n columns.The eigenvalues λ of a matrix A are scalars such that Ax = λx for some nonzero x vector.The entries aij of a matrix A are the numbers contained within the matrix, each with a unique position of the ith row and jth column.'Equality' in matrices has the same definition as for the rest of mathematics.A matrix of groups is a matrix whose entries are members of a group, often with specific entries in certain positions.The matrix identity In is that square n by n matrix whose entries aij are 1 if i = j, and 0 if i ≠j.The inverse of a square matrix A is the square matrix B such that AB = In, denoted by B = A-1.Matrix multiplication is the act of combining two matrices, the p-by-q A = (aij) and the q-by-r B = (bij) to form the new matrix p-by-r C = (cij) such that cij = Σaikbkj, where 1 ≤ k ≤ q. This is denoted by C = AB. Note that matrix mulplication is not commutative, i.e. AB does not necessarily equal BA; the order of the components is important and must be maintained to achieve the result. Note also that although p does not need to equal r, q must be the same in each matrix.
ya yes its there a matrix called zero matrix
A sparse matrix is a matrix in which most of the elements are zero.
A zero matrix is a matrix in which all of the entries are zero.
a squar matrix A is called involutary matrix. if A^2=I