|
Showing 1 - 3 of
3 matches in All Departments
Tensors have numerous applications in physics and engineering.
There is often a fuzzy haze surrounding the concept of tensor that
puzzles many students. The old-fashioned definition is difficult to
understand because it is not rigorous; the modern definitions are
difficult to understand because they are rigorous but at a cost of
being more abstract and less intuitive.The goal of this book is to
elucidate the concepts in an intuitive way but without loss of
rigor, to help students gain deeper understanding. As a result,
they will not need to recite those definitions in a parrot-like
manner any more. This volume answers common questions and corrects
many misconceptions about tensors. A large number of illuminating
illustrations helps the reader to understand the concepts more
easily.This unique reference text will benefit researchers,
professionals, academics, graduate students and undergraduate
students.
This book presents a concise exposition of modern mathematical
concepts, models and methods with applications in computer
graphics, vision and machine learning. The compendium is organized
in four parts - Algebra, Geometry, Topology, and Applications. One
of the features is a unique treatment of tensor and manifold topics
to make them easier for the students. All proofs are omitted to
give an emphasis on the exposition of the concepts. Effort is made
to help students to build intuition and avoid parrot-like
learning.There is minimal inter-chapter dependency. Each chapter
can be used as an independent crash course and the reader can start
reading from any chapter - almost. This book is intended for upper
level undergraduate students, graduate students and researchers in
computer graphics, geometric modeling, computer vision, pattern
recognition and machine learning. It can be used as a reference
book, or a textbook for a selected topics course with the
instructor's choice of any of the topics.
This book presents a concise exposition of modern mathematical
concepts, models and methods with applications in computer
graphics, vision and machine learning. The compendium is organized
in four parts - Algebra, Geometry, Topology, and Applications. One
of the features is a unique treatment of tensor and manifold topics
to make them easier for the students. All proofs are omitted to
give an emphasis on the exposition of the concepts. Effort is made
to help students to build intuition and avoid parrot-like
learning.There is minimal inter-chapter dependency. Each chapter
can be used as an independent crash course and the reader can start
reading from any chapter - almost. This book is intended for upper
level undergraduate students, graduate students and researchers in
computer graphics, geometric modeling, computer vision, pattern
recognition and machine learning. It can be used as a reference
book, or a textbook for a selected topics course with the
instructor's choice of any of the topics.
|
|