v2010.10.26 - Convex Optimization

716 APPENDIX E. PROJECTIONE.5.0.0.2 Example. Orthogonal projection on span of nonorthogonal basis.Orthogonal projection on a subspace can also be accomplished by projectingnonorthogonally on the individual members of any nonorthogonal basis forthat subspace. This interpretation is in fact the principal application of thepseudoinverse we discussed. Now suppose matrix A holds a nonorthogonalbasis for R(A) in its columns,A = [a 1 a 2 · · · a n ] ∈ R m×n (1927)and define the rows a ∗Ti of its pseudoinverse A † as in (1928). Thenorthogonal projection of vector x∈ R n on R(A) is a sum of one-dimensionalnonorthogonal projectionsPx = AA † x =n∑i=1a i a ∗Ti x (1938)where each nonsymmetric dyad a i a ∗Ti is a nonorthogonal projector projectingon R(a i ) , (E.6.1) idempotent because of biorthogonality condition A † A = I .The projection Px is regarded as the best approximation to x from theset R(A) , as it was in Example E.5.0.0.1.E.5.0.0.3 Example. Biorthogonal expansion as nonorthogonal projection.Biorthogonal expansion can be viewed as a sum of components, each anonorthogonal projection on the range of an extreme direction of a pointedpolyhedral cone K ; e.g., Figure 163.Suppose matrix A∈ R m×n holds a nonorthogonal basis for R(A) inits columns as in (1927), and the rows of pseudoinverse A † are definedas in (1928). Assuming the most general biorthogonality condition(A † + BZ T )A = I with BZ T defined as for (1886), then biorthogonalexpansion of vector x is a sum of one-dimensional nonorthogonal projections;for x∈ R(A)x = A(A † + BZ T )x = AA † x =n∑i=1a i a ∗Ti x (1939)where each dyad a i a ∗Ti is a nonorthogonal projector projecting on R(a i ).(E.6.1) The extreme directions of K=cone(A) are {a 1 ,..., a n } the linearlyindependent columns of A , while the extreme directions {a ∗ 1 ,..., a ∗ n}