Titlebook: Neural Nets; 14th Italian Worksho Bruno Apolloni,Maria Marinaro,Roberto Tagliaferri Conference proceedings 2003 Springer-Verlag Berlin Heid

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Lattice Models for Context-Driven Regularization in Motion Perceptionerty. By checking the presence of such Gestalts in optic flow fields we can make their interpretation more confident. We propose a context-sensitive recurrent filter capable of evidencing motion Gestalts corresponding to 1st-order elementary flow components (EFCs). A Gestalt emerges from a noisy flo

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On the Dynamics of Scale-Free Boolean Networksuced. RBN are known to display two major dynamical behaviours, depending upon the value of some model parameters, In the ”ordered” regime the number of attractors is a growing polynomial function of the number of nodes N, while in the ”chaotic” regime the growth is exponential. We present here a mod

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An Algorithm to Model Paradigm Shifting in Fuzzy Clusteringopose an implementation of a graded possibilistic clustering algorithm based on an interval equality constraint enforcing both the normality condition and the required graded possibilistic condition. Experimental results highlight the different properties attainable through appropriate implementatio

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ANFIS Synthesis by Hyperplane Clustering for Time Series Predictionredicted. ANFIS networks are neural models particularly suited to the solution of such problems, which usually require a data driven estimation technique. In this context, clustering procedures represent a straightforward approach to the synthesis of ANFIS networks. A novel use of clustering, workin

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