Maria Marinaro / Roberto Tagliaferri (eds.)

Neural Nets

13th Italian Workshop on Neural Nets, WIRN VIETRI 2002, Vietri sul Mare, Italy, May 30-June 1, 2002. Revised Papers
Herausgegeben:Marinaro, Maria; Tagliaferri, Roberto

• Broschiertes Buch

Produktbeschreibung

This volume contains the proceedings of the 13th Italian Workshop on Neural Nets WIRN VIETRI 2002, jointly organized by the International Institute for Advanced Scienti?c Studies Eduardo R. Caianiello (IIASS), the Societ`aIt- iana Reti Neuroniche (SIREN), the IEEE NNC Italian RIG, and the Italian SIG of the INNS. In this book a review talk, dealing with a very up-to-date topic Ensembles of Learning Machines , and original contributions, approved by the referee c- mittee as oral or poster presentations, have been collected. The contributions have been assembled, for reading convenience, into sections. The last section, devoted to Learning in Neural Networks: Limitations and Future Trends ,wasorganizedbyProf.M. Goriandalsocontainstheinvitedl- ture Mathematical Modeling of Generalization given by Dr. Martin Anthony. The ?rst and second sections are dedicated, respectively, to the memory of two scientists who were friends in life, Professors Francesco Lauria and Eduardo R. Caianiello. The editors thank all the participants for their quali?ed contributions, while special thanks go to Prof. M. Gori for his help in the organization, and to the referees for their accurate work. July 2002 MariaMarinaro RobertoTagliaferri Organizing Scienti?cCommittee B. Apolloni (Univ. Milano), A. Bertoni (Univ. Milano), N. A. Borghese (Univ. Milano), D. D. Caviglia (Univ. Genova), P. Campadelli (Univ. Milano), A. Chella (Univ. Palermo), A. Colla (ELSAG Genova), A. Esposito (I.I.A.S.S.), C.

Produktdetails

• Lecture Notes in Computer Science 2486
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 10870619, 978-3-540-44265-3
• 2002
• Seitenzahl: 272
• Erscheinungstermin: 27. September 2002
• Englisch
• Abmessung: 235mm x 155mm x 15mm
• Gewicht: 386g
• ISBN-13: 9783540442653
• ISBN-10: 3540442650
• Artikelnr.: 23380490

Autorenporträt

Maria Marinaro, International Institute for Advanced Scientific Studies "E.R. Caianiello" - IIASS, Vietri Sul Mare, Italy / Roberto Tagliaferri, University of Salerno, Italy

Inhaltsangabe

Review Papers.- Ensembles of Learning Machines.- Eduardo R. Caianiello Lecture.- Learning Preference Relations from Data.- Francesco E. Lauria Lecture.- Increasing the Biological Inspiration of Neural Networks.- Architectures and Algorithms.- Hybrid Automatic Trading Systems: Technical Analysis & Group Method of Data Handling.- Interval TOPSIS for Multicriteria Decision Making.- A Distributed Algorithm for Max Independent Set Problem Based on Hopfield Networks.- Extended Random Neural Networks.- Generalized Independent Component Analysis as Density Estimation.- Spline Recurrent Neural Networks for Quad-Tree Video Coding.- MLP Neural Network Implementation on a SIMD Architecture.- Image and Signal Processing.- A New Approach to Detection of Muscle Activation by Independent Component Analysis and Wavelet Transform.- Learning to Balance Upright Posture: What can be Learnt Using Adaptive NN Models?.- Detection of Facial Features.- A Two Stage Neural Architecture for Segmentation and Superquadrics Recovery from Range Data.- Automatic Discrimination of Earthquakes and False Events in Seismological Recording for Volcanic Monitoring.- A Comparison of Signal Compression Methods by Sparse Solution of Linear Systems.- Fuzzy Time Series for Forecasting Pollutants Concentration in the Air.- Real-Time Perceptual Coding of Wideband Speech by Competitive Neural Networks.- Sound Synthesis by Flexible Activation Function Recurrent Neural Networks.- Special Session on "Learning in Neural Networks: Limitations and Future Trends" Chaired by Marco Gori.- Mathematical Modelling of Generalization.- Structural Complexity and Neural Networks.- Bayesian Learning Techniques: Application to Neural Networks with Constraints on Weight Space.- A Short Review of Statistical Learning Theory.-Increasing the Biological Inspiration of Neural Networks.