Organized in a practical problem-and-solution format, More Exceptional C++ picks up where the widely acclaimed Exceptional C++ leaves off, providing successful strategies for solving real-world problems in C++. Drawing from years of in-the-trenches experience, Herb Sutter provides tested techniques and practical solutions for programmers designing modern software systems with C++, from small projects to enterprise applications.
DEMO_COND demonstrates the role of the condition
number of a matrix (with respect to inversion)
in the role of linear system solving.
Matthias Heinkenschloss
Department of Computational and Applied Mathematics
Rice University
Feb 22, 2001
MATSNL is a package of MATLAB M-files for computing wireless sensor node lifetime/power budget and solving optimal node architecture choice problems. It is intended as an analysis and simulation tool for researchers and educators that are easy to use and modify. MATSNL is designed to give the rough power/ lifetime predictions based on node and application specifications while giving useful insight on platform design for the large node lifetime by providing side-by-side comparison across various platforms. The MATSNL code and manual can be found at the bottom of this page. A related list of publications describing the models used in MATSNL is posted on the ENALAB part of the 2 project at http://www.eng.yale.edu/enalab/aspire.htm
MATSNL is a package of MATLAB M-files for computing wireless sensor node
lifetime/power budget and solving optimal node architecture choice problems. It is intended
as an analysis and simulation tool for researchers and educators that are easy to use and
modify. MATSNL is designed to give the rough power/ lifetime predictions based on node
and application specifications while giving useful insight on platform design for the large
node lifetime by providing side-by-side comparison across various platforms.
This book is about 3D math, the study of the mathematics behind the geometry of a 3D world. 3D
math is related to computational geometry, which deals with solving geometric problems algorithmically.
3D math and computational geometry have applications in a wide variety of fields that use computers to model or reason about the world in 3D, such as graphics, games, simulation,
robotics, virtual reality, and cinematography.
This book covers theory and practice in C++.
Evolutionary Computation (EC) deals with problem solving, optimization, and
machine learning techniques inspired by principles of natural evolution and ge-
netics. Just from this basic definition, it is clear that one of the main features of
the research community involved in the study of its theory and in its applications
is multidisciplinarity. For this reason, EC has been able to draw the attention of
an ever-increasing number of researchers and practitioners in several fields.
This book is intended for RF planners, to serve as a practical tool in their daily work
designing indoor radio distribution systems.
Based on feedback from readers of the first edition it was clear to me that I needed to add
more material and in depth description of the basics of indoor systems based on using
repeaters; this has grown into a new Section 4.7.
There was also a strong demand to add more detail and dedicate a full chapter to radio
planning in tunnels, for both rail and road tunnels; and redundancy principles in the design
focus for solving the challenge of handover zones. An entire Chapter 11 is now dedicated to
tunnel radio planning.
Theartofcomputationofelectromagnetic(EM)problemshasgrownexponentially
for three decades due to the availability of powerful computer resources. In spite of
this, the EM community has suffered without a suitable text on the computational
techniques commonly used in solving EM-related problems. Although there have
been monographs on one particular technique or another, the monographs are written
for the experts rather than students. Only a few texts cover the major techniques and
dothatinamannersuitableforclassroomuse.Itseemsexpertsinthisareaarefamiliar
with one or a few techniques but not many seem to be familiar with all the common
techniques. This text attempts to fill that gap.
Control systems are becoming more important every day. At the beginning, the in-
dustry used sequential controls for solving a lot of industrial applications in control
systems, and then the linear systems gave us a huge increase in applying automatic
linear control on industrial application. One of the most recent methods for control-
ling industrial applications is intelligent control, which is based on human behavior
or concerning natural process.
