The support vector machine (SVM) is a supervised learning method that generates input-output mapping functions from a set of labeled training data. The mapping function can be either a classification function, i.e., the category of the input data, or a regression function. For classification, nonlinear kernel functions are often used to...
Geospatial development links your data to places on the Earth’s surface. Writing geospatial programs involves tasks such as grouping data by location, storing and analyzing large amounts of spatial information, performing complex geospatial calculations, and drawing colorful interactive maps. In order to do this well, you’ll need...
This book describes one design for the optimization and code-generation phases of such a compiler. Many compiler books are available for describing the analysis of programming languages. They emphasize the processes of lexical analysis, parsing, and semantic analysis. Several books are also available for describing compilation processes for...
In 2004, Joel Cohen published a paper in the Public Library of Science (PLoS) Biology, titled
“Mathematics is Biology’s Next Microscope, only Better; Biology is Mathematics’ Next Physics,
Only Better”. The premise of the article was that in the near future there will be an explosion in
both math and biology...
To help solve physical and engineering problems, mimetic or compatible algebraic discretization methods employ discrete constructs to mimic the continuous identities and theorems found in vector calculus. Mimetic Discretization Methods focuses on the recent mimetic discretization method co-developed by the first author. Based...
This manual is intended to provide guidance towards the preparation
and testing of elementary function subroutines for non-vector oriented
digital computers. We believe it will be useful to systems programmers,
teachers, students of numerical analysis, hobbyists and anyone else
concerned or curious about how the elementary...
A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning
A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible...
This book reminds students in junior, senior and graduate level courses in physics, chemistry and engineering of the math they may have forgotten (or learned imperfectly), which is needed to succeed in science courses. The focus is on math actually used in physics, chemistry and engineering, and the approach to mathematics begins with 12...
Mathematics for Electrical Engineering and Computing embraces many applications of modern mathematics, such as Boolean Algebra and Sets and Functions, and also teaches both discrete and continuous systems - particularly vital for Digital Signal Processing (DSP). In addition, as most modern engineers are required to study software,...
Your hands-on guide to real-world applications of linear algebra
Does linear algebra leave you feeling lost? No worries —this easy-to-follow guide explains the how and the why of solving linear algebra problems in plain English. From matrices to vector spaces to linear transformations, you'll understand the key concepts and see how...
Plugins will soon be a thing of the past. The Definitive Guide to HTML5 Video is the first authoritative book on HTML5 Video, the new web standard that allows browsers to support audio and video elements natively. This makes it very easy for web developers to publish audio and video, integrating both within the general presentation...
