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...

This book provides a concise guide to current IP Multicast technology and its applications, with a focus on IP-based Television (IPTV) and Digital Video Broadcast-Handheld (DVB-H) applications—areas of tremendous commercial...

Ecologists sometimes have a less-than-rigorous background in quantitative methods, yet research within this broad field is becoming increasingly mathematical. Written in a step-by-step fashion, Fractals and Multifractals in Ecology and...

Assuming only background knowledge of algebra and elementary calculus, and access to a modern personal computer, Nonlinear Computer Modeling of Chemical and Biochemical Data presents the fundamental basis and procedures of data modeling by computer using nonlinear regression analysis. Bypassing the need for intermediary analytical...

Studying and using light or "photons" to image and then to control and transmit molecular information is among the most challenging and significant research fields to emerge in recent years. One of the fastest growing areas involves research in the temporal imaging of quantum phenomena, ranging from molecular dynamics in the femto...

Unlike other analytic techniques, the Homotopy Analysis Method (HAM) is independent of small/large physical parameters. Besides, it provides great freedom to choose equation type and solution expression of related linear high-order approximation equations. The HAM provides a simple way to guarantee the convergence of solution series. Such...