Page 135 - 35Linear Algebra
P. 135

7.3 Properties of Matrices                                                                    135


                   Example 83 Graphs occur in many applications, ranging from telephone networks to
                   airline routes. In the subject of graph theory, a graph is just a collection of vertices
                   and some edges connecting vertices. A matrix can be used to indicate how many edges
                   attach one vertex to another.




















                   For example, the graph pictured above would have the following matrix, where m i
                                                                                                j
                   indicates the number of edges between the vertices labeled i and j:

                                                                
                                                       1 2 1 1
                                                       2 0 1 0
                                                                
                                                M =             
                                                      1 1 0 1   
                                                       1 0 1 3
                                                                       j
                                                                 i
                   This is an example of a symmetric matrix, since m = m .
                                                                       i
                                                                 j
                                          Adjacency Matrix Example



                      The set of all r × k matrices

                                               i
                                           i
                                  r
                               M := {(m )|m ∈ R; i ∈ {1, . . . , r}; j ∈ {1 . . . k}} ,
                                  k
                                               j
                                           j
                   is itself a vector space with addition and scalar multiplication defined as
                   follows:
                                                                          i
                                                      i
                                                                    i
                                                             i
                                        M + N = (m ) + (n ) = (m + n )
                                                                    j
                                                                          j
                                                             j
                                                      j
                                                                   i
                                                          i
                                               rM = r(m ) = (rm )
                                                                   j
                                                          j
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