Written by two leading authorities in the field, this self-contained volume provides a tutorial on projection methods and how to apply them in science and engineering. It details effective problem-solving strategies, and explores key applications in communication and signal processing, neural networks and pattern recognition, and optics and image processing. This book reviews the fundamentals of vector space theory, covers principles and applications of vector space projections in general, and projections onto convex sets in particular, provides real-world examples solvable on PCs and modest workstations, features more than 100 illustrations, and includes end-of-chapter exercises and references. This useful reference for practicing engineers, scientists, and educators can also be used for graduate-level study in science, mathematics, and engineering. Portions of the book have been used as material in short courses on applications of vector space projections.
Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics
