Series : Mathematics and Visualization
2004, XII, 437 pp. With 19 colour figs., Hardcover
ISBN: 3-540-21462-3
Due: August 2004
About this book
Multiresolution methods in geometric modelling are concerned with
the generation, representation, and manipulation of geometric
objects at several levels of detail. Applications include fast
visualization and rendering as well as coding, compression, and
digital transmission of 3D geometric objects. This book marks the
culmination of the four-year EU-funded research project,
Multiresolution in Geometric Modelling (MINGLE). The book
contains seven survey papers, providing a detailed overview of
recent advances in the various aspects of multiresolution
modelling, and sixteen additional research papers. Each of the
seven parts of the book starts with a survey paper, followed by
the associated research papers in that area. All papers were
originally presented at the MINGLE 2003 workshop held at Emmanuel
College, Cambridge, UK, 9-11 September 2003.
Written for:
Scientists, professionals and graduate students in computer
graphics, surface modelling, geometry processing, surface
parameterization, wavelets, subdivision, data structures,
geometry compression, visualization, thinning
Keywords:
compression
computer graphics
geometry
modeling
parameterization
surfaces
2004, Approx. 800 p., Hardcover
ISBN: 3-540-21460-7
Due: August 9, 2004
About this book
The book is the Proceedings of the Conference ENUMATH 2003, the 5th
European Conference on Numerical Mathematics, concerned with most
recent achievements in scientific computing, computational
mathematics, numerical analysis and their applications. These
proceedings contain a selection of invited plenary lectures,
papers presented in minisymposia and contributed papers. All
contributions to these proceedings have been reviewed by members
of the Scientific Committee. Attention is paid to theoretical
aspects of new numerical techniques and algorithms, as well as to
applications, for example in fluid dynamics, electromagnetic
fields, structural mechanics, free boundary problems. The book
will be very useful for a wide range of readers, giving them an
excellent overview of the most modern methods, techniques,
algorithms and results in numerical mathematics, scientific
computing and their applications.
Written for:
Computational scientists
Keywords:
computational fluid dynamics
computational mathematics
computational physics
numerical analysis
scientific computing
Series : Springer Texts in Statistics
2004, Approx. 800 p., Hardcover
ISBN: 0-387-40270-5
Due: August 2004
About this book
This contemporary presentation of statistical methods features
extensive use of graphical displays for exploring data and for
displaying the analysis. The authors demonstrate how to construct
and interpret graphs, discuss principles of graphical design, and
show how accompanying traditional tabular results are used to
confirm the visual impressions derived directly from the graphs.
Many of the graphical formats are novel and appear here for the
first time in print. This book can serve as a standalone text for
statistics majors at the master's level and for other
quantitatively oriented disciplines at the doctoral level, and as
a reference book for researchers. In-depth discussions of
regression analysis, analysis of variance, and design of
experiments are followed by introductions to analysis of discrete
bivariate data, nonparametrics, logistic regression, and ARIMA
time series modeling. The authors illustrate classical concepts
and techniques with a variety of case studies using both newer
graphical tools and traditional tabular displays. The authors
provide and discuss S-Plus, R, and SAS executable functions and
macros for all new graphical display formats. All graphs and
tabular output in the book were constructed using these programs.
Complete transcripts for all examples and figures are provided
for readers to use as models for their own analyses. Richard M.
Heiberger and Burt Holland are both Professors in the Department
of Statistics at Temple University and elected Fellows of the
American Statistical Association. Richard M. Heiberger
participated in the design of the S-Plus linear model and
analysis of variance commands while on research leave at Bell
Labs in 1987?88 and has been closely involved as a beta tester
and user of S-Plus. Burt Holland has made many research
contributions to linear modeling and simultaneous statistical
inference, and frequently serves as a consultant to medical
investigators. Both teach the Temple University course sequence
that inspired them to write this text.
Table of contents
Introduction and Motivation.- Data and Statistics.- Statistics
Concepts.- Graphs.- Introductory Inference.- One-Way Analysis of
Variance, ANOVA.- Multiple Comparisons.- Linear Regression by
Least Squares.- Multiple Regression - More Than One Predictor.-
Multiple Regression - Dummy Variables and Contrasts.- Multiple
Regression - Regression Diagnostics.- Two-Way Analysis of
Variance.- Design of Experiments - Factorial Designs.- Design of
Experiments - More Complex Designs.- Bivariate Statistics -
Discrete Data.- Nonparametrics.- Logistic Regression.- Time
Series Analysis.
Series : Springer Texts in Statistics
2004, XIII, 252 p., Hardcover
ISBN: 0-387-20332-X
Due: July 2004
About this textbook
Finite-dimensional optimization problems occur throughout the
mathematical sciences. The majority of these problems cannot be
solved analytically. This introduction to optimization attempts
to strike a balance between presentation of mathematical theory
and development of numerical algorithms. Building on students’
skills in calculus and linear algebra, the text provides a
rigorous exposition without undue abstraction. Its stress on
convexity serves as bridge between linear and nonlinear
programming and makes it possible to give a modern exposition of
linear programming based on the interior point method rather than
the simplex method. The emphasis on statistical applications will
be especially appealing to graduate students of statistics and
biostatistics. The intended audience also includes graduate
students in applied mathematics, computational biology, computer
science, economics, and physics as well as upper division
undergraduate majors in mathematics who want to see rigorous
mathematics combined with real applications. Chapter 1 reviews
classical methods for the exact solution of optimization problems.
Chapters 2 and 3 summarize relevant concepts from mathematical
analysis. Chapter 4 presents the Karush-Kuhn-Tucker conditions
for optimal points in constrained nonlinear programming. Chapter
5 discusses convexity and its implications in optimization.
Chapters 6 and 7 introduce the MM and the EM algorithms widely
used in statistics. Chapters 8 and 9 discuss Newton’s method
and its offshoots, quasi-Newton algorithms and the method of
conjugate gradients. Chapter 10 summarizes convergence results,
and Chapter 11 briefly surveys convex programming, duality, and
Dykstra’s algorithm. Kenneth Lange is the Rosenfeld Professor
of Computational Genetics in the Departments of Biomathematics
and Human Genetics at the UCLA School of Medicine. He is also
Interim Chair of the Department of Human Genetics. At various
times during his career, he has held appointments at the
University of New Hampshire, MIT, Harvard, the University of
Michigan, and the University of Helsinki. While at the University
of Michigan, he was the Pharmacia & Upjohn Foundation
Professor of Biostatistics. His research interests include human
genetics, population modeling, biomedical imaging, computational
statistics, and applied stochastic processes. Springer-Verlag
previously published his books Mathematical and Statistical
Methods for Genetic Analysis, 2nd ed., Numerical Analysis for
Statisticians, and Applied Probability.
Table of contents
Elementary Optimization.- The Seven C's of Analysis.-
Differentiation.- Karush-Kuhn-Tucker Theory.- Convexity.- The MM
Algorithm.- The EM Algorithm.- Newton's Method.- Conjugate
Gradient and Quasi-Newton.- Analysis of Convergence.- Convex
Programming.
Series : Texts and Monographs in Physics
2004, XIII, 441 p. 102 illus., Hardcover
ISBN: 3-540-21320-1
Due: August 24, 2004
About this textbook
Many-Body Problems and Quantum Field Theory introduces the
concepts and methods of the topics on a level suitable for
graduate students and researchers. The formalism is developed in
close conjunction with the description of a number of physical
systems: cohesion and dielectric properties of the electron gas,
superconductivity, superfluidity, nuclear matter and nucleon
pairing, matter and radiation, interaction of fields by particle
exchange and mass generation. Emphasis is placed on analogies
between the various systems rather than on advanced or
specialized aspects, with the purpose of illustrating common
ideas within different domains of physics. Starting from a basic
knowledge of quantum mechanics and classical electromagnetism,
the exposition is self-contained and explicitly details all steps
of the derivations. The new edition features a subtantially new
treatment of nucleon pairing.
Written for:
Students (2nd year and after)
Keywords:
Bose Gas
Einstein-Bose Condensation
Electronic Gas
Hartree-Fock Method
N-Body Problem
Nuclear Structure
Perturbative Methods in Field Theory
Superconductivite
Superfluidity
Series : Texts in Theoretical Computer Science. An EATCS
Series
2004, Approx. 400 p., Hardcover
ISBN: 3-540-21146-2
Due: October 2004
About this textbook
The book addresses ways and means of organizing computations,
highlighting the relationship between algorithms and the basic
mechanisms and runtime structures necessary to execute them using
machines. It completely abstracts from concrete programming
languages and machine architectures, taking instead the lambda
calculus as the basic programming and program execution model to
design various abstract machines for its correct implementation.
The emphasis is on strongly normalizing machines based on a full-fledged
beta-reduction as an essential prerequisite for symbolic
computations that treat functions and variables truly as first-class
objects. Their weakly normalizing counterparts are shown to be
functional abstract machines that sacrifice the flavors of full
beta-reductions for decidedly simpler runtime structures and
improved runtime efficiency. Further downgrading of the lambda
calculus leads to classical imperative (von Neumann) machines
that permit side-effecting operations on the runtime environment.
Table of contents
Preliminary Table of Contents: Algorithms and Programs.- An
Algorithmic Language.- The Lambda Calculus.- the SE(M)CD-Machine.-
Towards Full-fledged Lambda Calculus Machines.- Head-order Graph
Reduction.- The B-Machine.- The G-Machine.- The p-RED Machinery.
Series : Encyclopaedia of Mathematical Sciences , Vol. 102
Volume package: Enc.Mathematical Sciences Mathematical Physics
2004, approx. 384 pp. 25 figs., Hardcover
ISBN: 3-540-22066-6
Due: August 2004
About this book
The notion of uniform hyperbolicity, introduced by Steve Smale in
the early sixties, unified important developments and led to a
remarkably successful theory for a large class of systems:
uniformly hyperbolic systems often exhibit complicated evolution
which, nevertheless, is now rather well understood, both
geometrically and statistically. Another revolution has been
taking place in the last couple of decades, as one tries to build
a global theory for "most" dynamical systems,
recovering as much as possible of the conclusions of the
uniformly hyperbolic case, in great generality. This book aims to
put such recent developments in a unified perspective, and to
point out open problems and likely directions for further
progress. It is aimed at researchers, both young and senior,
willing to get a quick, yet broad, view of this part of dynamics.
Main ideas, methods, and results are discussed, at variable
degrees of depth, with references to the original works for
details and complementary information.
Table of contents
1 Hyperbolicity and Beyond.- 2 One-Dimensional Dynamics.- 3
Homoclinic Tangencies.- 4 Henon-like Dynamics.- 5 Non-critical
Dynamics and Hyperbolicity.- 6 Heterodimensional Cycles and
Blenders.- 7 Robust Transitivity.- 8 Stable Ergodicity.- 9 Robust
Singular Dynamics.- 10 Generic Diffeomorphisms.- 11 SRB Measures
and Gibbs States.- 12 Lyapunov Exponents.- A Perturbation Lemmas.-
B Normal Hyperbolictiy and Foliations.- C Non-uniformly
Hyperbolic Theory.- D Random Perturbations.- E Decay of
Correlations.- Conclusion.- References.- Index