Beschreibung:
1. The Inverse of a Nonsingular Matrix It is well known that every nonsingular matrix A has a unique inverse, ?1 denoted by A , such that ?1 ?1 AA = A A =I, (1) where I is the identity matrix. Of the numerous properties of the inverse matrix, we mention a few. Thus, ?1 ?1 (A ) = A, T ?1 ?1 T (A ) =(A ) , ? ?1 ?1 ? (A ) =(A ) , ?1 ?1 ?1 (AB) = B A , T ? where A and A , respectively, denote the transpose and conjugate tra- pose of A. It will be recalled that a real or complex number ? is called an eigenvalue of a square matrix A, and a nonzero vector x is called an eigenvector of A corresponding to ?,if Ax = ?x. ?1 Another property of the inverse A is that its eigenvalues are the recip- cals of those of A. 2. Generalized Inverses of Matrices A matrix has an inverse only if it is square, and even then only if it is nonsingular or, in other words, if its columns (or rows) are linearly in- pendent. In recent years needs have been felt in numerous areas of applied mathematics for some kind of partial inverse of a matrix that is singular or even rectangular.
The field of generalized inverses has grown much since the appearanceof the first edition in 1974, and is still growing. This bookaccounts for these developments while maintaining the informal andleisurely style of the first edition. New material has been addedincluding a chapter on applications, an appendixo on the work of E.H.Moore, new exercises and applications.
Preliminaries.- Existence and Construction of Generalized Inverses.- Linear Systems and Characterization of Generalized Inverses.- Minimal Properties of Generalized Inverses.- Spectral Generalized Inverses.- Generalized Inverses of Partitioned Matrices.- A Spectral Theory for Rectangular Matrices.- Computational Aspects of Generalized Inverses.- Miscellaneous Applications.- Generalized Inverses of Linear Operators between Hilbert Spaces.