Focusing on Bayesian approaches and computations using
simulation-based methods for inference, Time Series:
Modeling, Computation, and Inference integrates
mainstream approaches for time series modeling with significant
recent developments in methodology and applications of time
series analysis. It encompasses a graduate-level account of
Bayesian time series modeling and analysis, a broad range of
references to state-of-the-art... more...

The near future will see the increased use of parallel computing
technologies at all levels of mainstream computing. Computer
hardware increasingly employs parallel techniques to improve
computing power for the solution of large-scale and
computer-intensive applications. Cluster and grid technologies make
possible high speed computing facilities at vastly reduced costs.
These developments can be expected to result in the extended use of
all types of... more...

An accessible guide to the multivariate time series tools used
in numerous real-world applications
Multivariate Time Series Analysis: With R and Financial
Applications is the much anticipated sequel coming from one
of the most influential and prominent experts on the topic of
time series. Through a fundamental balance of theory and
methodology, the book supplies readers with a comprehensible
approach to financial econometric models... more...

Focusing on growth and decay processes, interacting populations,
and heating/cooling problems, Mathematical Modelling with
Case Studies: A Differential Equations Approach using
Maple™ and MATLAB®, Second
Edition presents mathematical techniques applicable
to models involving differential equations that describe rates of
change. Although the authors concentrate on models involving
differential equations, the ideas used can be applied... more...

Introduction to the Calculus of Variations and Control
with Modern Applications provides the fundamental
background required to develop rigorous necessary conditions that
are the starting points for theoretical and numerical approaches
to modern variational calculus and control problems. The book
also presents some classical sufficient conditions and discusses
the importance of distinguishing between the necessary and
sufficient... more...

This book is a rigorous exposition of formal languages and models
of computation, with an introduction to computational complexity.
The authors present the theory in a concise and straightforward
manner, with an eye out for the practical applications. Exercises
at the end of each chapter, including some that have been solved,
help readers confirm and enhance their understanding of the
material. This book is appropriate for upper-level computer science... more...

Miller and Childers have focused on creating a clear presentation
of foundational concepts with specific applications to signal
processing and communications, clearly the two areas of most
interest to students and instructors in this course. It is aimed at
graduate students as well as practicing engineers, and includes
unique chapters on narrowband random processes and simulation
techniques.
The appendices provide a refresher in such areas as linear... more...

This work deals with the theory and some applications of integral
transforms that involve integration with respect to an index or
parameter of a special function of the hypergeometric type as the
kernel (index transforms). The basic index transforms are
considered, such as the Kontorovich-Lebedev transform, the
Mehler-Fock transform, the Olevskii Transform and the
Lebedev-Skalskaya transforms. The Lp theory of index transforms is
discussed, and new... more...

Geometry lies at the core of the architectural design process. It is omnipresent, from the initial determination of form to the final construction. Modern geometric computing provides a variety of tools for the efficient design, analysis, and manufacturing of complex shapes. On the one hand this opens up new horizons for architecture. On the other, the architectural context also poses new problems for geometry. The research area of architectural... more...

Continuous-time Markov decision processes (MDPs), also known as controlled Markov chains, are used for modeling decision-making problems that arise in operations research (for instance, inventory, manufacturing, and queueing systems), computer science, communications engineering, control of populations (such as fisheries and epidemics), and management science, among many other fields. This volume provides a unified, systematic, self-contained... more...