E-Book, Englisch, Band 2486, 252 Seiten, eBook
Marinaro / Tagliaferri Neural Nets
Erscheinungsjahr 2003
ISBN: 978-3-540-45808-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
13th Italian Workshop on Neural Nets, WIRN VIETRI 2002, Vietri sul Mare, Italy, May 30-June 1, 2002. Revised Papers
E-Book, Englisch, Band 2486, 252 Seiten, eBook
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-540-45808-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
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.
