Neural Nets [electronic resource] : 13th Italian Workshop on Neural Nets, WIRN VIETRI 2002 Vietri sul Mare, Italy, May 30 – June 1, 2002 Revised Papers / edited by Maria Marinaro, Roberto Tagliaferri.

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.