Computational and Ambient Intelligence (eBook, PDF)

9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastián, Spain, June 20-22, 2007, Proceedings
Redaktion: Sandoval, Francisco; Graña, Manuel; Cabestany, Joan; Prieto, Alberto

• Format: PDF

Produktbeschreibung

We present in this volume the collection of finally accepted papers for the ninth e- tion of the IWANN conference ("International Work-Conference on Artificial Neural Networks"). This biennial meeting focuses on the foundations, theory, models and applications of systems inspired by nature (neural networks, fuzzy logic and evo- tionary systems). Since the first edition of IWANN in Granada (LNCS 540, 1991), the computational intelligence community and the domain itself have matured and evolved. Under the computational intelligent banner we find a very heterogeneous scenario with a main interest and objective: to better understand nature and natural entities for the correct elaboration of theories, models and new algorithms. For scientifics, engineers and professionals working in the area, this is a very good way to get real, solid and c- petitive applications. More and more, these new computational techniques are used in applications that try to bring a new situation of well-being to the user. The conjunction of a more and more miniaturized hardware together with the growing computational intelligence embodied in this hardware leads us towards fully integrated embedded systems-on- chip and opens the door for truly ubiquitous electronics.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 1167
• Erscheinungstermin: 21. September 2007
• Englisch
• ISBN-13: 9783540730071
• Artikelnr.: 44224441

Autorenporträt

Francisco Sandoval, Universidad de Málaga, Spain / Alberto Prieto, Universidad de Granada, Spain / Joan Cabestany, Universitat Politècnica de Catalunya, Barcelona, Spain / Manuel Graña, Universidad del País Vasco, San Sebastian, Spain

Inhaltsangabe

Theoretical Concepts and Neuro Computational Formulations.- Improving Models and Learning Procedures.- Self-organizing Networks.- Kernel Methods.- Evolutionary and Genetic Algorithms.- Evolutionary Learning.- Fuzzy Systems.- Neuroingeniering and Hardware Implementations.- Data Analysis.- Signal Processing.- Speech Processing.- Image Processing.- Time Series and Prediction.- Robotics and Planning Motor Control.- Power System Applications.- Internet and Web Applications.- Biomedical Applications.- Neural Networks and Other Machine Learning Methods in Cancer Research.- Assistive Technologies and e-Health.- Other Applications.