467 | Chapter 6 Outline |
Sections, concepts, and problems
6.1. Inner products and norms.
Inner products and their properties, two standard examples (the standard inner
product on Fn and the Frobenius inner product on the set of n by n
matrices over F), the conjugate transpose of a matrix, the norm of a vector in
an inner product space, orthogonal vectors, unit vectors, orthonormal vectors.
6.2. Gram-Schmidt orthogonalization process.
Orthonormal bases, why we care about them, how to transform an arbitrary basis
into an orthogonal basis, Fourier coefficients, orthogonal complements.
6.3. The adjoint of a linear operator.
(Assume V is finite-dimensional.)
How every linear functional is an inner product with a fixed y in V,
what an adjoint of a linear operator on V is, what it has to do with
conjugate transposes of matrices, properties of adjoints, and an application to
least squares approximations.
6.4. Normal and self-adjoint operators.
Normal linear operators and matrices, various properties of these, what normal
operators have to do with orthonormal bases and eigenvectors, self-adjoint (or
Hermitian [her-me-shun]) linear operators and matrices, and various
properties of these.
6.5. Unitary and orthogonal operators and their matrices.
Unitary/orthogonal operators, properties they possess, conditions their
eigenvalues have, orthogonal/unitary matrices, examples of rotations and
reflections of the plane, unitary/orthogonal equivalence of matrices, rigid
motions, and an application to quadratic forms.
Other ChaptersChapter 1 | Chapter 2 | Chapter 3 | Chapter 4 | Chapter 5 | Chapter 6 |