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!