Page 348 - Advanced Linear Algebra
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332    Advanced Linear Algebra















                                       Figure 13.1
                                                                            ,
            Let us see what we can learn about this sequence. First, if we let &~ % c
            then according to the parallelogram law,
                          )      )&b     b  )&       )&c &       )  ) ~  ²     )&    ) b &       ³

            or

                         )      )&c &       )  ) ~  ²     )&    ) b &       ³ c   h  &b &      h  (13.2 )

            Now, if the set   is convex , that is, if
                        :
                         %Á &  : ¬  % b ²  c  ³&  : for all       
            (in  words,    contains  the line segment between any two of its points ), then
                     :
            ²  b   ³°   : and so


                                &b &             b
                               h      h  ~%          h c  ‚
                                          h

            Thus, 13.2  gives
                 (
                     )
                           )      )&c &       )  )   ²     )&    ) b &       ³ c       ¦
            as   Á   ¦ B .  Hence,  if    is convex, then the sequence  ²& ³ ~ ²% c   ³  is a
                                :


            Cauchy sequence and therefore so is ²  ³ .

            If we also require that   be complete, then the Cauchy sequence     ²    ³   converges
                              :
                                                                  )
                                                                      V
            to a vector %:  and by the continuity of the norm, we must have  % c % ~   .
                     V
                                                                       )
            Let us summarize and add a remark about uniqueness.
            Theorem 13.9 Let   be an inner product space and let   be a complete convex
                                                         :
                           =
                   =
            subset of  . Then for any    %  =  , there exists a unique    V  :   for which
                                                        %
                                   )    V )%c% ~ inf )  )%c
                                             :
            The vector   is called the best approximation  to   in  .
                     %
                                                        :
                                                    % V
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