Excerpt from Implementation of the Schnabel and Eskow Modified Cholesky Factorization in the Context of a Truncated-Newton Optimization Method
Two important questions in these modified factorizations are the following: 1) how do we perform the mcf in a numerically-stable manner without knowing the complete eigenvalue distribution of M a priori? And 2) how do we choose the appropriate numerical values for the entries of E? The first issue is important because the Cholesky factors may be ill-conditioned and may not exist for an indefinite system; thus, the standard process must be amended appropriately. Furthermore, the algorithm should be formulated so as to keep the computational cost as close as possible to that of the standard Cholesky factorization. In regard to the second question of constructing E, we must generate a clever recipe for choosing the increments ci, j n, so as to balance: 1) on one extreme, selecting large modifications that guarantee positive definiteness but perturb the original matrix excessively; with 2) on the other extreme, choosing small, just sufficient.
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Paperback. Condición: New. Print on Demand. This book delves into the fascinating world of nonlinear optimization, a field that seeks to find the best solutions to complex problems where the relationships between variables are not simple. The author specifically focuses on a technique known as the Modified Cholesky Factorization (MCF), a powerful tool for solving large, sparse systems of equations that arise in various scientific disciplines. The book compares two popular MCF implementations: the Gill, Murray, and Wright (GMW) method and the Schnabel & Eskow (S&E) method. While both factorizations have been widely used in the context of nonlinear optimization, this book explores their differences in performance and highlights how the S&E method may be particularly advantageous for dealing with highly indefinite systems, those that exhibit a complex combination of positive and negative values. The book analyzes various numerical experiments to demonstrate how each approach tackles the challenges of finding solutions for different types of problems, and concludes with a compelling argument for the S&E method as a potentially more efficient and robust tool for solving the types of complex equations that arise in fields like computational chemistry and mathematical biology. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Nº de ref. del artículo: 9781332868841_0
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781332868841
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781332868841
Cantidad disponible: 15 disponibles