Apolloni / Tagliaferri / Marinaro | Biological and Artificial Intelligence Environments | Buch | 978-90-481-6863-7 | sack.de

Buch, Englisch, 406 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 628 g

Apolloni / Tagliaferri / Marinaro

Biological and Artificial Intelligence Environments

Buch, Englisch, 406 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 628 g

ISBN: 978-90-481-6863-7
Verlag: Springer Netherlands


The book reports the proceedings of the 15th Italian workshop on neural networks issued by the Italian Society on Neural Networks SIREN. The longevity recipe of this conference stands in three main points that normally renders the reading of these proceedings so interesting as appealing. 1. The topics of the neural networks is considered an attraction pole for a set of researches centered on the inherent paradigm of the neural networks, rather than on a specific tool exclusively. Thus, the subsymbolic management of the data information content constitutes the key feature of papers in various fields such as Pattern Recognition, Stochastic Optimization, Learning, Granular Computing, and so on, with a special bias toward bioinformatics operational applications. An excerpt of all these matters may be found in the book. 2. Though managed at domestic level, the conference attracts contributions from foreign researchers as well, so that in the book the reader may capture the flavor of the state of the art in the international community. 3. The conference is a meeting of friends as well. Thus the papers generally reflect a relaxed atmosphere where researchers meet to generously exchange their thought and explain their actual results in view of a common cultural growing of the community.
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Pre-Wirn workshop on Computational Intelligence Methods for Bioinformatics and Bistatistics (CIBB).- Progengrid: A Grid Framework for Bioinformatics.- A Preliminary Investigation on Connecting Genotype to Oral Cancer Development through XCS.- Mass Spectrometry Data Analysis for Early Detection of Inherited Breast Cancer.- Feature Selection Combined with Random Subspace Ensemble for Gene Expression Based Diagnosis of Malignancies.- Pruning the Nodule Candidate Set in Postero Anterior Chest Radiographs.- Protein Structure Assembly from Knowledge of ?-Sheet Motifs and Secondary Structure.- Analysis of Oligonucleotide Microarray Images Using a Fuzzy Sets Approach in HLA Typing.- Combinatorial and Machine Learning Approaches in Clustering Microarray Data.- Gene Expression Data Modeling and Validation of Gene Selection Methods.- Mining Yeast Gene Microarray Data with Latent Variable Models.- Recent Applications of Neural Networks in Bioinformatics.- Pre-WIRN workshop on Computational Intelligence on Hardware: Algorithms, Implementations and Applications (CIHAIA).- An Algorithm for Reducing the Number of Support Vectors.- Genetic Design of Linear Block Error-Correcting Codes.- Neural Hardware Based on Kernel Methods for Industrial and Scientific Applications.- Stratistical Learning for Parton Identification.- Time-Varying Signals Classification Using a Liquid State Machine.- FPGA Based Statistical Data Mining Processor.- Neural Classification of HEP Experimental Data.- WIRN Regular Sessions Architectures and Algorithms.- The Random Neural Network Model for the On-Line Multicast Problem.- ERAF: A R Package for Regression and Forecasting.- Novel Pheromone Updating Strategy for Speeding up ACO Applied to VRP.- Inducing Communication Protocols from Conversations in a Multi AgentSystem.- Wordnet and Semidiscrete Decomposition for Sub-Symbolic Representation of Words.- The Hopfield and Kohonen Networks: an in Vivo Test.- Support Vector Regression with a Generalized Quadratic Loss.- A Flexible ICA Approach to a Novel BSS Convolutive Nonlinear Problem: Preliminary Results.- Models.- Computing Confidence Intervals for the Risk of A SVM Classifier through Algorithmic Inference.- Learning Continuous Functions through a New Linear Regression Method.- A Novel Kernel Method for Clustering.- Genetic Monte Carlo Markov Chains.- Consistency of Empirical Risk Minimization for Unbounded Loss Functions.- A Probabilistic PCA Clustering Approach to the SVD Estimate of Signal Subspaces.- Fast Dominant-Set Clustering.- Neural Network Classification Using Error Entropy Minimization.- Applications.- An ICA Approach to Unsupervised Change Detection in Multispectral Images.- A Comparison of ICA Algorithms in Biomedical Signal Processing.- Time-Frequency Analysis for Characterizing EMG Signals During fMRI Acquisitions.- A Neural Algorithm for Object Positioning in 3D Space Using Optoelectronic System.- Human Visual System Modelling for Real-Time Salt and Pepper Noise Removal.- Virtual Sensors to Support the Monitoring of Cultural Heritage Damage.- A Computer Aided Analysis on Digital Images.- Recursive Neural Networks for the Classification of Vehicles in Image Sequences.- Neural Network in Modeling Glucose-Insulin Behavior.- Assessing the Reliability of Communication Networks Through Maghine Learning Techniques.- Dynamical Reconstruction and Chaos for Disruption Prediction in Tokamak Reactors.


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