Cloth | 2005 | ISBN: 0-691-12231-8
272 pp. | 5 1/2 x 8 1/2 | 12 tables.
The great logician Gottlob Frege attempted to provide a purely
logical foundation for mathematics. His system collapsed when
Bertrand Russell discovered a contradiction in it. Thereafter,
mathematicians and logicians, beginning with Russell himself,
turned in other directions to look for a framework for modern
abstract mathematics. Over the past couple of decades, however,
logicians and philosophers have discovered that much more is
salvageable from the rubble of Frege's system than had previously
been assumed. A variety of repaired systems have been proposed,
each a consistent theory permitting the development of a
significant portion of mathematics.
This book surveys the assortment of methods put forth for fixing
Frege's system, in an attempt to determine just how much of
mathematics can be reconstructed in each. John Burgess considers
every proposed fix, each with its distinctive philosophical
advantages and drawbacks. These systems range from those barely
able to reconstruct the rudiments of arithmetic to those that go
well beyond the generally accepted axioms of set theory into the
speculative realm of large cardinals. For the most part, Burgess
finds that attempts to fix Frege do less than advertised to
revive his system. This book will be the benchmark against which
future analyses of the revival of Frege will be measured.
John P. Burgess is Professor of Philosophy at Princeton
University. He is the author of numerous articles on mathematical
and philosophical logic and philosophy of mathematics and
coauthor of A Subject with No Object.
Reviews:
"This book is without match. I suspect that it will be used
both as a general introduction to the subject and as a source on
particular topics for years to come."--Kit Fine, New York
University
"I suspect that this will become a must-read among those
working in the philosophy of mathematics and the foundations of
mathematics. It will most certainly be a significant contribution
to the field."--Stewart Shapiro, Ohio State University
Cloth | August 2005 | ISBN: 0-691-12327-6
200 pp. | 6 x 9
This book places thermodynamics on a system-theoretic foundation
so as to harmonize it with classical mechanics. Using the highest
standards of exposition and rigor, the authors develop a novel
formulation of thermodynamics that can be viewed as a moderate-sized
system theory as compared to statistical thermodynamics. This
middle-ground theory involves deterministic large-scale dynamical
system models that bridge the gap between classical and
statistical thermodynamics.
The authors' theory is motivated by the fact that a discipline as
cardinal as thermodynamics--entrusted with some of the most
perplexing secrets of our universe--demands far more than
physical mathematics as its underpinning. Even though many great
physicists, such as Archimedes, Newton, and Lagrange, have
humbled us with their mathematically seamless eurekas over the
centuries, this book suggests that a great many physicists and
engineers who have developed the theory of thermodynamics seem to
have forgotten that mathematics, when used rigorously, is the
irrefutable pathway to truth.
This book uses system theoretic ideas to bring coherence,
clarity, and precision to an extremely important and poorly
understood classical area of science.
Wassim M. Haddad is Professor of Aerospace Engineering at the
Georgia Institute of Technology. VijaySekhar Chellaboina is
Associate Professor in the Department of Mechanical, Aerospace,
and Biomedical Engineering at the University of Tennessee,
Knoxville. Sergey G. Nersesov is a Ph.D. student in aerospace
engineering at Georgia Institute of Technology.
Endorsements:
"This is an original contribution to the important, but very
diverse, field of thermodynamics. The book's self-contained
system-theoretic approach makes it accessible to a wide audience
of readers."--Jan Willems, University of Gronigen
"This is a truly original and fundamental contribution to
the field of thermodynamics. It will make a lasting contribution
to the literature."--Naira Hovakimyan, Virginia Polytechnic
Institute and State University
Series: Advanced Information and Knowledge Processing
2005, 272 p. 101 illus., Hardcover
ISBN: 1-85233-867-9
About this book
This book presents research on some of the most recent advances
in data mining and knowledge discovery, providing theory as well
as its applications on practical real world applications. The
methodologies discussed encompass tools like Bayesian networks,
and major facets of computational intelligence paradigms.
Table of contents
Trends in Data Mining and Knowledge Discovery Advanced Methods
for the Analysis of Semiconductor Manufacturing Process Data
Clustering and visualization of Retail Market Baskets
Segmentation Of Continuous Data Streams Based on a Change
Detection Methodology Instance Selection Using Evolutionary
Algorithms: An Experimental Study Using Cooperative Coevolution
for Data Mining of Bayesian Networks Knowledge Discovery and Data
Mining in Medicine Satellite Image Classification Using Cascaded
Architecture of Neural Fuzzy Network Discovery of Positive and
Negative Rules from Medical Databases based on Rough Sets
Series: Springer Series in Statistics
2005, XXII, 434 p. 151 illus., Hardcover
ISBN: 0-387-40080-X
About this book
Scientists today collect samples of curves and other functional
observations. This monograph presents many ideas and techniques
for such data. Included are expressions in the functional domain
of such classics as linear regression, principal components
analysis, linear modelling, and canonical correlation analysis,
as well as specifically functional techniques such as curve
registration and principal differential analysis. Data arising in
real applications are used throughout for both motivation and
illustration, showing how functional approaches allow us to see
new things, especially by exploiting the smoothness of the
processes generating the data. The data sets exemplify the wide
scope of functional data analysis; they are drwan from growth
analysis, meterology, biomechanics, equine science, economics,
and medicine. The book presents novel statistical technology
while keeping the mathematical level widely accessible. It is
designed to appeal to students, to applied data analysts, and to
experienced researchers; it will have value both within
statistics and across a broad spectrum of other fields. Much of
the material is based on the authors' own work, some of which
appears here for the first time. Jim Ramsay is Professor of
Psychology at McGill University and is an international authority
on many aspects of multivariate analysis. He draws on his
collaboration with researchers in speech articulation, motor
control, meteorology, psychology, and human physiology to
illustrate his technical contributions to functional data
analysis in a wide range of statistical and application journals.
Bernard Silverman, author of the highly regarded "Density
Estimation for Statistics and Data Analysis," and coauthor
of "Nonparametric Regression and Generalized Linear Models:
A Roughness Penalty Approach," is Professor of Statistics at
Bristol University. His published work on smoothing methods and
other aspects of applied, computational, and theoretical
statistics has been recognized by the Presidents' Award of the
Committee of Presidents of Statistical Societies, and the award
of two Guy Medals by the Royal Statistical Society.
Table of contents
Introduction * Notation and Techniques * Representing Functional
Data as Smooth Functions * The Roughness Penalty Approach * The
Registration and Display of Functional Data * Principal
Components Analysis for Functional Data * Regularized Principal
Components Analysis * Principal Components Analysis of Mixed Data
* Functional Linear Models * Functional Linear Models for Scalar
Responses * Functional Linear Modesl for Functional Responses *
Canonical Correlation and Discriminant Analysis * Differential
Operators in Functional Data Analysis * Principal Differential
Analysis * More General Roughness Penalties * Some Perspectives
on FDA
Series: Natural Computing Series
2005, XIII, 173 p., Hardcover
ISBN: 3-540-65773-8
About this book
This book provides a broad overview of the entire field of DNA
computation, tracing its history and development. It contains
detailed descriptions of all major theoretical models and
experimental results to date, which are lacking in existing
texts, and discusses potential future developments. It also
provides a useful reference source for researchers and students,
and an accessible introduction for people new to the field.
The field of DNA computation has flourished since the publication
of Adleman's seminal article, in which he demonstrated for the
first time how a computation may be performed at a molecular
level by performing standard operations on a tube of DNA strands.
This monograph provides a detailed survey of the field, before
describing recent theoretical and experimental developments. It
concludes by outlining the challenges faced by researchers in the
field and suggests possible future directions.
Table of contents