Introduction into the matrix theory
Definition of matrix. By matrix A we mean a rectangular array of numbers
The matrix A consists of m horizontal n-tuples
(a11, a12, ..., a1n), (a21, a22, ..., a2n), ..., (am1, am2, ..., amn),
called rows of A, and of the n vertical m-tuples
called its columns. Note that the element aij called ij-entry, appears in the i-th row and the j-th column. We frequently denote such a matrix simply by A = (aij).
A matrix with m rows and n columns is said to be an m by n matrix, written m ´ n. The pair of numbers m and n is called the size of the matrix. Two matrices A and B are equal, written A = B, if they have the same size and if corresponding elements are equal.
It is possible to perform addition and multiplication of matrices.
Square matrix. A matrix with the same number of rows and as columns is called a square matrix. A square matrix with n rows and n columns is said to be of order n, and is called an n-square matrix. The main diagonal, or simply diagonal, of a square matrix A = (aij) consists of the numbers
(a11, a22, ..., ann).
Unit matrix. The n-square matrix with 1's along the main diagonal and 0'd elsewhere, e.g.
is called the unit or identity matrix and will be denoted by I. The unit matrix I plays the same role in matrix multiplication as the number 1 does in the usual multiplication of numbers. Specifically,
AI = IA = A.
for any square matrix A.
The square matrixes can be raised to a power. We can define powers of the square matrix A as following:
A2 = AA, A3 = A2A, ..., A0 = I.
Inverse matrix. A square matrix A is said to be invertible if there exists a matrix B with the property that
AB = BA = I.
Such a matrix B is unique; it is called the inverse of A and is denoted by A-1.
Determinants. To each n-square matrix A = (aij) we assign a specific number called the determinant of A, denoted by Det (A) or |A|.
The determinants of order one and two are defined as follows:
Det (a11) = |a11|= a11
An important property of the determinant is given with the following theorem.
Theorem. For any two n-square matrices A and B we have
Det (AB) = (Det A) ´ (Det B).
It follows from this theorem that
Det (An) = (Det A)n.
After this preliminary introduction we can go on to Fibonacci matrices. And we will begin from the simplest Fibonacci matrix, called Q-matrix. Follow us!