Page 51 - Matrix Analysis & Applied Linear Algebra
P. 51

44               Chapter 2                      Rectangular Systems and Echelon Forms

                                        Notice that the final result of applying Gaussian elimination in the above
                                    example is not a purely triangular form but rather a jagged or “stair-step” type
                                    of triangular form. Hereafter, a matrix that exhibits this stair-step structure will
                                    be said to be in row echelon form.


                                                           Row Echelon Form
                                       An m × n matrix E with rows E i∗ and columns E ∗j is said to be in
                                       row echelon form provided the following two conditions hold.

                                       •   If E i∗ consists entirely of zeros, then all rows below E i∗ are also
                                           entirely zero; i.e., all zero rows are at the bottom.

                                       •   If the first nonzero entry in E i∗ lies in the j th  position, then all
                                           entries below the i th  position in columns E ∗1 , E ∗2 ,..., E ∗j are zero.

                                       These two conditions say that the nonzero entries in an echelon form
                                       must lie on or above a stair-step line that emanates from the upper-
                                       left-hand corner and slopes down and to the right. The pivots are the
                                       first nonzero entries in each row. A typical structure for a matrix in row
                                       echelon form is illustrated below with the pivots circled.
                                                                                   
                                                           *  ∗  ∗   ∗   ∗ ∗   ∗   ∗
                                                        0   0   *   ∗   ∗ ∗   ∗   ∗ 
                                                        0   0   0    *  ∗ ∗   ∗   ∗ 
                                                       
                                                                                    
                                                        0   0   0   0   0 0   *   ∗ 
                                                                                    
                                                       
                                                         0   0   0   0   0 0   0   0
                                                                                   
                                                         0   0   0   0   0 0   0   0
                                        Because of the flexibility in choosing row operations to reduce a matrix A
                                    to a row echelon form E, the entries in E are not uniquely determined by A.
                                    Nevertheless, it can be proven that the “form” of E is unique in the sense that
                                    the positions of the pivots in E (and A) are uniquely determined by the entries
                                          9
                                    in A .  Because the pivotal positions are unique, it follows that the number of
                                    pivots, which is the same as the number of nonzero rows in E, is also uniquely
                                                                                            10
                                    determined by the entries in A . This number is called the rank  of A, and it
                                  9
                                    The fact that the pivotal positions are unique should be intuitively evident. If it isn’t, take the
                                    matrix given in (2.1.1) and try to force some different pivotal positions by a different sequence
                                    of row operations.
                                 10
                                    The word “rank” was introduced in 1879 by the German mathematician Ferdinand Georg
                                    Frobenius (p. 662), who thought of it as the size of the largest nonzero minor determinant
                                    in A. But the concept had been used as early as 1851 by the English mathematician James
                                    J. Sylvester (1814–1897).
   46   47   48   49   50   51   52   53   54   55   56