|
|
Books > Science & Mathematics > Mathematics
First Semester Calculus for Students of Mathematics and Related
Disciplines equips students with a strong working knowledge of the
fundamental principles of calculus, providing an engaging and
accessible entry point into this critical field of study. It
prepares students for more advanced courses in calculus and also
helps them understand how to apply basic principles of calculus to
solve problems within a wide range of disciplines, including
business, biology, engineering, science, liberal arts and, of
course, mathematics. The text employs rigorous treatment of early
calculus topics and detailed explanations to facilitate deeper
understanding of later material. Over the course of five chapters,
students learn about symbolic logic, continuity and limits,
derivatives, antiderivatives, and applications of each. Throughout,
students are provided with rich guidance and copious opportunities
to deepen their personal understanding of the subject matter. In
the second edition, a more efficient layout better highlights major
theorems and definitions. Additionally, over 300 new exercises have
been added to further aid student learning. Highly readable and
innovative, yet pedagogically solid and very applicable, First
Semester Calculus for Students of Mathematics and Related
Disciplines is an ideal resource for a variety of courses that
apply concepts of calculus to solve mathematical and real-world
problems.
INTRODUCTION TO LINEAR REGRESSION ANALYSIS A comprehensive and
current introduction to the fundamentals of regression analysis
Introduction to Linear Regression Analysis, 6th Edition is the most
comprehensive, fulsome, and current examination of the foundations
of linear regression analysis. Fully updated in this new sixth
edition, the distinguished authors have included new material on
generalized regression techniques and new examples to help the
reader understand retain the concepts taught in the book. The new
edition focuses on four key areas of improvement over the fifth
edition: New exercises and data sets New material on generalized
regression techniques The inclusion of JMP software in key areas
Carefully condensing the text where possible Introduction to Linear
Regression Analysis skillfully blends theory and application in
both the conventional and less common uses of regression analysis
in today's cutting-edge scientific research. The text equips
readers to understand the basic principles needed to apply
regression model-building techniques in various fields of study,
including engineering, management, and the health sciences.
Evolution of Knowledge Science: Myth to Medicine: Intelligent
Internet-Based Humanist Machines explains how to design and build
the next generation of intelligent machines that solve social and
environmental problems in a systematic, coherent, and optimal
fashion. The book brings together principles from computer and
communication sciences, electrical engineering, mathematics,
physics, social sciences, and more to describe computer systems
that deal with knowledge, its representation, and how to deal with
knowledge centric objects. Readers will learn new tools and
techniques to measure, enhance, and optimize artificial
intelligence strategies for efficiently searching through vast
knowledge bases, as well as how to ensure the security of
information in open, easily accessible, and fast digital networks.
Author Syed Ahamed joins the basic concepts from various
disciplines to describe a robust and coherent knowledge sciences
discipline that provides readers with tools, units, and measures to
evaluate the flow of knowledge during course work or their
research. He offers a unique academic and industrial perspective of
the concurrent dynamic changes in computer and communication
industries based upon his research. The author has experience both
in industry and in teaching graduate level telecommunications and
network architecture courses, particularly those dealing with
applications of networks in education.
Uncertainties in GPS Positioning: A Mathematical Discourse
describes the calculations performed by a GPS receiver and the
problems associated with ensuring that the derived location is a
close match to the actual location. Inaccuracies in calculating a
location can have serious repercussions, so this book is a timely
source for information on this rapidly evolving technology.
Exterior Algebras: Elementary Tribute to Grassmann's Ideas provides
the theoretical basis for exterior computations. It first addresses
the important question of constructing (pseudo)-Euclidian
Grassmmann's algebras. Then, it shows how the latter can be used to
treat a few basic, though significant, questions of linear algebra,
such as co-linearity, determinant calculus, linear systems
analyzing, volumes computations, invariant endomorphism
considerations, skew-symmetric operator studies and decompositions,
and Hodge conjugation, amongst others.
Mathematics for Neuroscientists, Second Edition, presents a
comprehensive introduction to mathematical and computational
methods used in neuroscience to describe and model neural
components of the brain from ion channels to single neurons, neural
networks and their relation to behavior. The book contains more
than 200 figures generated using Matlab code available to the
student and scholar. Mathematical concepts are introduced hand in
hand with neuroscience, emphasizing the connection between
experimental results and theory.
Basic Optics: Principles and Concepts addresses in great detail the
basic principles of the science of optics, and their related
concepts. The book provides a lucid and coherent presentation of an
extensive range of concepts from the field of optics, which is of
central relevance to several broad areas of science, including
physics, chemistry, and biology. With its extensive range of
discourse, the book's content arms scientists and students with
knowledge of the essential concepts of classical and modern optics.
It can be used as a reference book and also as a supplementary text
by students at college and university levels and will, at the same
time, be of considerable use to researchers and teachers. The book
is composed of nine chapters and includes a great deal of material
not covered in many of the more well-known textbooks on the
subject. The science of optics has undergone major changes in the
last fifty years because of developments in the areas of the optics
of metamaterials, Fourier optics, statistical optics, quantum
optics, and nonlinear optics, all of which find their place in this
book, with a clear presentation of their basic principles. Even the
more traditional areas of ray optics and wave optics are elaborated
within the framework of electromagnetic theory, at a level more
fundamental than what one finds in many of the currently available
textbooks. Thus, the eikonal approximation leading to ray optics,
the Lagrangian and Hamiltonian formulations of ray optics, the
quantum theoretic interpretation of interference, the vector and
dyadic diffraction theories, the geometrical theory of diffraction,
and similar other topics of basic relevance are presented in clear
terms. The presentation is lucid and elegant, capturing the
essential magic and charm of physics. All this taken together makes
the book a unique text, of major contemporary relevance, in the
field of optics. Avijit Lahiri is a well-known researcher, teacher,
and author, with publications in several areas of physics, and with
a broad range of current interests, including physics and the
philosophy of science.
Nature-Inspired Optimization Algorithms provides a systematic
introduction to all major nature-inspired algorithms for
optimization. The book's unified approach, balancing algorithm
introduction, theoretical background and practical implementation,
complements extensive literature with well-chosen case studies to
illustrate how these algorithms work. Topics include particle swarm
optimization, ant and bee algorithms, simulated annealing, cuckoo
search, firefly algorithm, bat algorithm, flower algorithm, harmony
search, algorithm analysis, constraint handling, hybrid methods,
parameter tuning and control, as well as multi-objective
optimization. This book can serve as an introductory book for
graduates, doctoral students and lecturers in computer science,
engineering and natural sciences. It can also serve a source of
inspiration for new applications. Researchers and engineers as well
as experienced experts will also find it a handy reference.
The author's goal is a rigorous presentation of the fundamentals of
analysis, starting from elementary level and moving to the advanced
coursework. The curriculum of all mathematics (pure or applied) and
physics programs include a compulsory course in mathematical
analysis. This book will serve as can serve a main textbook of such
(one semester) courses. The book can also serve as additional
reading for such courses as real analysis, functional analysis,
harmonic analysis etc. For non-math major students requiring math
beyond calculus, this is a more friendly approach than many
math-centric options.
|
|