Solving Dense Nonlinear Least-squares Problems on a Multiprocessor PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Solving Dense Nonlinear Least-squares Problems on a Multiprocessor PDF full book. Access full book title Solving Dense Nonlinear Least-squares Problems on a Multiprocessor by Thomas Frederick Coleman. Download full books in PDF and EPUB format.
Author: Thomas Frederick Coleman
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 64
Get Book Here
Book Description
Author: Thomas Frederick Coleman
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 64
Get Book Here
Book Description
Author: James W. Demmel
Publisher: SIAM
ISBN: 0898713897
Category : Mathematics
Languages : en
Pages : 426
Get Book Here
Book Description
This comprehensive textbook is designed for first-year graduate students from a variety of engineering and scientific disciplines.
Author: Ake Bjorck
Publisher: SIAM
ISBN: 9781611971484
Category : Mathematics
Languages : en
Pages : 425
Get Book Here
Book Description
The method of least squares was discovered by Gauss in 1795. It has since become the principal tool to reduce the influence of errors when fitting models to given observations. Today, applications of least squares arise in a great number of scientific areas, such as statistics, geodetics, signal processing, and control. In the last 20 years there has been a great increase in the capacity for automatic data capturing and computing. Least squares problems of large size are now routinely solved. Tremendous progress has been made in numerical methods for least squares problems, in particular for generalized and modified least squares problems and direct and iterative methods for sparse problems. Until now there has not been a monograph that covers the full spectrum of relevant problems and methods in least squares. This volume gives an in-depth treatment of topics such as methods for sparse least squares problems, iterative methods, modified least squares, weighted problems, and constrained and regularized problems. The more than 800 references provide a comprehensive survey of the available literature on the subject.
Author: Johan A. K. Suykens
Publisher: Springer Science & Business Media
ISBN: 9780792381952
Category : Language Arts & Disciplines
Languages : en
Pages : 284
Get Book Here
Book Description
This collection of eight contributions presents advanced black-box techniques for nonlinear modeling. The methods discussed include neural nets and related model structures for nonlinear system identification, enhanced multi-stream Kalman filter training for recurrent networks, the support vector method of function estimation, parametric density estimation for the classification of acoustic feature vectors in speech recognition, wavelet based modeling of nonlinear systems, nonlinear identification based on fuzzy models, statistical learning in control and matrix theory, and nonlinear time- series analysis. The volume concludes with the results of a time- series prediction competition held at a July 1998 workshop in Belgium. Annotation copyrighted by Book News, Inc., Portland, OR.
Author: Thomas Frederick Coleman
Publisher: SIAM
ISBN: 9780898712681
Category : Mathematics
Languages : en
Pages : 278
Get Book Here
Book Description
Papers from a workshop held at Cornell University, Oct. 1989, and sponsored by Cornell's Mathematical Sciences Institute. Annotation copyright Book News, Inc. Portland, Or.
Author: Wen Shen
Publisher: World Scientific
ISBN: 9811204438
Category : Mathematics
Languages : en
Pages : 339
Get Book Here
Book Description
This book serves as a set of lecture notes for a senior undergraduate level course on the introduction to numerical computation, which was developed through 4 semesters of teaching the course over 10 years. The book requires minimum background knowledge from the students, including only a three-semester of calculus, and a bit on matrices.The book covers many of the introductory topics for a first course in numerical computation, which fits in the short time frame of a semester course. Topics range from polynomial approximations and interpolation, to numerical methods for ODEs and PDEs. Emphasis was made more on algorithm development, basic mathematical ideas behind the algorithms, and the implementation in Matlab.The book is supplemented by two sets of videos, available through the author's YouTube channel. Homework problem sets are provided for each chapter, and complete answer sets are available for instructors upon request.The second edition contains a set of selected advanced topics, written in a self-contained manner, suitable for self-learning or as additional material for an honored version of the course. Videos are also available for these added topics.
Author: Luigi Grippo
Publisher: Springer Nature
ISBN: 3031267907
Category : Mathematics
Languages : en
Pages : 721
Get Book Here
Book Description
This book has two main objectives: • to provide a concise introduction to nonlinear optimization methods, which can be used as a textbook at a graduate or upper undergraduate level; • to collect and organize selected important topics on optimization algorithms, not easily found in textbooks, which can provide material for advanced courses or can serve as a reference text for self-study and research. The basic material on unconstrained and constrained optimization is organized into two blocks of chapters: • basic theory and optimality conditions • unconstrained and constrained algorithms. These topics are treated in short chapters that contain the most important results in theory and algorithms, in a way that, in the authors’ experience, is suitable for introductory courses. A third block of chapters addresses methods that are of increasing interest for solving difficult optimization problems. Difficulty can be typically due to the high nonlinearity of the objective function, ill-conditioning of the Hessian matrix, lack of information on first-order derivatives, the need to solve large-scale problems. In the book various key subjects are addressed, including: exact penalty functions and exact augmented Lagrangian functions, non monotone methods, decomposition algorithms, derivative free methods for nonlinear equations and optimization problems. The appendices at the end of the book offer a review of the essential mathematical background, including an introduction to convex analysis that can make part of an introductory course.
Author: Christodoulos A. Floudas
Publisher: Springer Science & Business Media
ISBN: 0387747583
Category : Mathematics
Languages : en
Pages : 4646
Get Book Here
Book Description
The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".
Author: George William Irwin
Publisher: IET
ISBN: 9780852968529
Category : Computers
Languages : en
Pages : 320
Get Book Here
Book Description
The aim is to present an introduction to, and an overview of, the present state of neural network research and development, with an emphasis on control systems application studies. The book is useful to a range of levels of reader. The earlier chapters introduce the more popular networks and the fundamental control principles, these are followed by a series of application studies, most of which are industrially based, and the book concludes with a consideration of some recent research.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 836
Get Book Here
Book Description
