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286              Chapter 5                    Norms, Inner Products, and Orthogonality
                   5.3 INNER-PRODUCT SPACES


                                    The euclidean norm, which naturally came first, is a coordinate-dependent con-
                                    cept. But by isolating its important properties we quickly moved to the more
                                    general coordinate-free definition of a vector norm given in (5.1.9) on p. 275. The
                                    goal is to now do the same for inner products. That is, start with the standard
                                    inner product, which is a coordinate-dependent definition, and identify proper-
                                    ties that characterize the basic essence of the concept. The ones listed below are
                                    those that have been distilled from the standard inner product to formulate a
                                    more general coordinate-free definition.


                                                        General Inner Product

                                       An inner product on a real (or complex) vector space V is a function
                                       that maps each ordered pair of vectors x, y to a real (or complex) scalar
                                        x y  such that the following four properties hold.
                                             x x  is real with  x x ≥ 0, and  x x  =0 if and only if x = 0,
                                             x αy  = α  x y  for all scalars α,
                                                                                                (5.3.1)
                                             x y + z  =  x y  +  x z  ,
                                             x y  =  y x   (for real spaces, this becomes  x y  =  y x ).
                                       Notice that for each fixed value of x, the second and third properties
                                       say that  x y  is a linear function of y.

                                       Any real or complex vector space that is equipped with an inner product
                                       is called an inner-product space.


                   Example 5.3.1

                                                                            T        n×1
                                                                                                       ∗
                                    •  The standard inner products,  x y  = x y for      and  x y  = x y
                                           n×1
                                       for C   , each satisfy the four defining conditions (5.3.1) for a general inner
                                       product—this shouldn’t be a surprise.
                                                                                 ∗
                                                                                    ∗
                                    •  If A n×n is a nonsingular matrix, then  x y  = x A Ay is an inner product
                                            n×1
                                       for C   . This inner product is sometimes called an A-inner product or
                                       an elliptical inner product.
                                    •  Consider the vector space of m × n matrices. The functions defined by
                                                              T
                                                                                          ∗
                                              A B  = trace A B      and    A B  = trace (A B)      (5.3.2)
                                                            m×n       m×n
                                       are inner products for    and C    , respectively. These are referred to
                                       as the standard inner products for matrices. Notice that these reduce
                                       to the standard inner products for vectors when n =1.
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