Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to rec

Presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object

This collection of eight contributions presents advanced black-box techniques for nonlinear modeling. The methods discussed include neural nets and related mode

Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students

This book analyzes the updated principles and applications of nonlinear approaches to solve engineering and physics problems. The knowledge on nonlinearity and