ARTIFICIAL NEURAL NETWORKS - ICANN 2007: 17TH INTERNATIONAL CONFERENCE, PORTO, PORTUGAL, SEPTEMBER 9-13, 2007, PROCEEDINGS

DANILO P. MANDIC, WLODZISLAW DUCH, JOAQUIM MARQUES DE SA

ISBN 10: 3540746897 / ISBN 13: 9783540746898

Published by SPRINGER, 2007

About this Item

Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

Seller Inventory # AD 9783540746898

Bibliographic Details

• Title: ARTIFICIAL NEURAL NETWORKS - ICANN 2007: 17TH INTERNATIONAL CONFERENCE, PORTO, PORTUGAL, SEPTEMBER 9-13, 2007, PROCEEDINGS
• Publisher: SPRINGER
• Publication Date: 2007
• Language: English
• ISBN 10: 3540746897
• ISBN 13: 9783540746898
• Binding: Paperback
• Edition: International Edition
• Condition: New

About this title

Synopsis

This book is the first of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007, held in Porto, Portugal, September 2007. Coverage includes advances in neural network learning methods, advances in neural network architectures, neural dynamics and complex systems, data analysis, evolutionary computing, agents learning, as well as temporal synchronization and nonlinear dynamics in neural networks.

From the Back Cover

This two volume set LNCS 4668 and LNCS 4669 constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007, held in Porto, Portugal, in September 2007.

The 197 revised full papers presented were carefully reviewed and selected from 376 submissions. The 98 papers of the first volume are organized in topical sections on learning theory, advances in neural network learning methods, ensemble learning, spiking neural networks, advances in neural network architectures neural network technologies, neural dynamics and complex systems, data analysis, estimation, spatial and spatio-temporal learning, evolutionary computing, meta learning, agents learning, complex-valued neural networks, as well as temporal synchronization and nonlinear dynamics in neural networks.