Targeted audience - Specialists in numerical computations, especially in
numerical optimiza- tion, who are interested in designing algorithms
with automatie result ver- ification, and who would therefore be
interested in knowing how general their algorithms caIi in principle
be. - Mathematicians and computer scientists who are interested in the
theory 0/ computing and computational complexity, especially
computational com- plexity of numerical computations. - Students in
applied mathematics and computer science who are interested in
computational complexity of different numerical methods and in learning
general techniques for estimating this computational complexity. The
book is written with all explanations and definitions added, so that it
can be used as a graduate level textbook. What this book .is about Data
processing. In many real-life situations, we are interested in the value
of a physical quantity y that is diflicult (or even impossible) to
measure directly. For example, it is impossible to directly measure the
amount of oil in an oil field or a distance to a star. Since we cannot
measure such quantities directly, we measure them indirectly, by
measuring some other quantities Xi and using the known relation between
y and Xi'S to reconstruct y. The algorithm that transforms the results
Xi of measuring Xi into an estimate fj for y is called data processing.