Multidimensional Data Visualization: Methods and Applications

The book provides recent research results in optimization-based visualization. Evolutionary algorithms and a two-level optimization method, based on combinatorial optimization and quadratic programming, are analyzed in detail. The performance of these algorithms and the development of parallel versions is discussed.

The encorporation of new visualization techniques to improve the capabilies of artificial neural networks (self-organizing maps, feed-forward networks) is also discussed.

The book includes over 100 detailed images presenting examples of the different visualization techniques that are presented.

This book is intended for scientists and researchers in any field of study where complex and multidimensional data must be represented visually.