Perspectives in Neural Computing

Section I Invited Papers: 1. On Sequential Bayesian Logistic Regression 2. Simple Reverberations and the Mind.- Section II Review Papers: 1. Computational Intelligence in Hydroinformatics: A Review 2. Theory, Implementation, and Applications of Support Vector Machines.- Section III Eduardo R Caianiello Lecture: Sensitivity Analysis and Learning of Non-Linear Dynamic Systems by Two Dual Signal-Flow-Graph Approaches.- Section IV Mathematical Models: 1. Interval Arithmetic Multilayer Perceptron as Possibility-Necessity Pattern Classifier 2.Polynomial Clusterons Exhibit Statistical Estimation Abilities 3. The N-SOBoS Nodel 4. A Neural Network Approach to Detect Functional MRI Signal 5. Continual Prediction Using LSTM with Forget Gates 6.Dynamics of On-Line Learning in Radial Basis Function Neural Networks 7. Harmony Theory and Binding Problem 8. Online Learning with Adaptive Local Step Sizes.- Section V Pattern Recognition and Signal Processing: 1. A Feed-Forward Neural Network for Robust Segmentation of Color Images 2. Parameter Identification Using Aspects - Application to the Human Cardiovascular System 3. A Neural Network Based ARX Model of Virgo Noise 4. Local Wavelet Decomposition and its Application to Face Reconstruction 5. A Multilayer Perceptron for Fast Interpolation of JPEG/MPEG Coded Images 6. The Automatic Detection of Microcalcification Clusters in the Calma Project: Status and Perspectives 7. Signal Classification by Subspace Neural Networks 8. Weightless Neural Networks for Face Recognition 9. The Search for Spiculated Lesions in the CALMA Project: Status and Perspectives 10. A Novel Wavelet Filtering Method in SAR Image Classification by Neural Networks 11. Neural Networks for Spectral Analysis of Unevenly Sampled Data.- Section VI Architectures and Algorithms: 1. Recursive Networks: An Overview of Theoretical Results.- 2.A Persistent and Parallel Approach to Object Oriented ANNs Simulators.- 3. An Experimental Comparison of Three PCA Neural Techniques.- 4. Scale Based Clustering Optimization via Gravitational Law Imitation.- 5. A General Assembly as Implementation of a Hebbian Rule in a Boolean Neural Network.- 6. Training Semiparametric Support Vector Machines.- 7. Building Neural and Logical Networks with Hamming Clustering.- 8.Inferring Understandable Rules Through Digital Synthesis.- 9. From Spiking Neurons to Dynamic Perceptrons.- 10. Using the Hermite Regression Algorithm to Improve the Generalization Capability of a Neural Network.- 11. Development of Selectivity Maps in a BCM Network Using Various Connectivity Schemes.- 12. An Analog On-Chip Learning Architecture Based on Weight Perturbation Algorithm and on Current Mode Translinear Circuits.- Section VII Applications: 1. Gesture Recognition Using Hybrid SOM/DHMM.- 2. A Fuzzy Neural Network for Urban Environment Monitoring System: The Villa San Giovanni Study Case.- 3. Real Time Neural Network Disruption Prediction in Tokamak Reactors.- 4. On-Line Quality Control of DC Permanent Magnet Motor Using Neural Networks.- Section VIII Neural Networks in Economics: 1. Fuzzy Local Algorithms for Time Series Analysis and Forecasting.- 2. Neural Networks Applications in Economics: A Statistical Point of View.- 3. Regional Economics Policy and Computational Economics.- 4. Neural Networks for Economic Forecasting.- 5. A Fuzzy Classification for the Definition of Industrial District.- 6. A Combination of Tools: NLS and NN Estimation of the Expenditures in Durables: Determinants, Trend and Forecasting for the Vehicles Sector.- 7. Estimating the Conditional Mean of a Non-Linear Time Series Using Neural Networks.