Practical Inverse Analysis in Engineering

by David M. Trujillo, Henry R. Busby

Continuing advances in computer technology have made it possible for engineers and scientists to construct increasingly realistic models of physical processes. Practical Inverse Analysis in Engineering addresses an important area of engineering that will become even more significant to engineers and scientists - combining measurements with engineering models. This self-contained text presents applied mathematical tools for bridging the gap between real-world measurements and mathematical models.The book demonstrates how to treat "ill-conditioned" inverse analysis problems - those problems where the solution is extremely sensitive to the data - with the powerful theory of dynamic programming. A second theory, generalized-cross-validation, is also discussed as a useful partner in handling real data. The material in the book, much of it published for the first time, presents theories in a general unified setting, so readers can apply the information to their models. A disk containing DYNAVAL programming software lets readers try the methods presented in the text.

Kindle Edition

First published October 22, 1997

Reviews

[Wangdo Kim · Rating 5 out of 5]

The exposition of dynamic programming by Richard Bellman gave hope those engaged in the analysis of complex systems, but it was said that this hope was diminished by the realization that more problems could be formulated by their technique than could be solved according to Ronald Howard. David Trujillo has made it possible for us to construct more realistic models of physiological processes by explicitly illustrating all details of dynamic programming.

The intent of this book is to provide an analytic structure for a decision-making system that is at the same time both general enough to be descriptive and yet computational feasible. It is based on the Markov process as a system model, and used an iterative technique similar to recurrence formulas as its optimization method.

This book addresses as important area of perceptual theory that will become even more significant in the future--identifying a perceptual system that must be at work that extracts invariant. By combining of external perception (exteroperception) with self coperception (proprioception), in this way, people are able to `tune into' their environment fairly automatically.