Distance in Graphs

This book provides an elementary treatment of the basic material about graph spectra, both for ordinary, and Laplace and Seidel spectra. It covers standard topics such as bounds on the sizes of cliques and cocliques, chromatic number and Shannon capacity, the connection between randomness and the 'eigenvalue gap', and applications.

This book gives an introduction to the field of Incidence Geometry by discussing the basic families of point-line geometries and introducing some of the mathematical techniques that are essential for their study.

Master the topics of the MikroTik MTCNA track using the theory & practical LABS and be ready for the MTCNA exam

This is a High School Mathematics Course for Students Preparing for iGCSE, GCSE & Secondary School Maths Exams

The ultimate supplement to learn pre-algebra at your own pace using the ALEKS math program.

Measurements, Density, Pressure, Forces, Motion Graphs, Moments, Springs, Momentum

In graph-based structural pattern recognition, the idea is to transform patterns into graphs and perform the analysis and recognition of patterns in the graph domain - commonly referred to as graph matching. A large number of methods for graph matching have been proposed. Graph edit distance, for instance, defines the dissimilarity of two graphs by the amount of distortion that is needed to transform one graph into the other and is considered one of the most flexible methods for error-tolerant graph matching.This book focuses on graph kernel functions that are highly tolerant towards structural errors.