Self-Organising Neural Networks: Independent Component Analysis and Blind Source Separation - Couverture souple

Girolami, Mark

Couverture souple

ISBN 10 : 185233066X ISBN 13 : 9781852330668

Editeur : Springer London, 1999

Synopsis

The conception of fresh ideas and the development of new techniques for Blind Source Separation and Independent Component Analysis have been rapid in recent years. It is also encouraging, from the perspective of the many scientists involved in this fascinating area of research, to witness the growing list of successful applications of these methods to a diverse range of practical everyday problems. This growth has been due, in part, to the number of promising young and enthusiastic researchers who have committed their efforts to expanding the current body of knowledge within this field of research. The author of this book is among one of their number. I trust that the present book by Dr. Mark Girolami will provide a rapid and effective means of communicating some of these new ideas to a wide international audience and that in turn this will expand further the growth of knowledge. In my opinion this book makes an important contribution to the theory of Independent Component Analysis and Blind Source Separation. This opens a range of exciting methods, techniques and algorithms for applied researchers and practitioner engineers, especially from the perspective of artificial neural networks and information theory. It has been interesting to see how rapidly the scientific literature in this area has grown.

Détails de l'édition

• Éditeur: Springer London
• Date d'édition: 1999
• Langue: anglais
• ISBN 10: 185233066X
• ISBN 13: 9781852330668
• Reliure: Broché
• Nombre de pages: 284
• Coordonnées du fabricant: non disponible
• Personne responsable: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Allemagne