Автор: Cesare Alippi; Marios M. Polycarpou; Christos Pana Название: Artificial Neural Networks – ICANN 2009 ISBN: 3642042767 ISBN-13(EAN): 9783642042768 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS).
Автор: Simone Bassis; Anna Esposito; Francesco Carlo Mora Название: Advances in Neural Networks: Computational and Theoretical Issues ISBN: 3319181637 ISBN-13(EAN): 9783319181639 Издательство: Springer Рейтинг: Цена: 22203.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems.
Описание: This book introduces selected recent findings on the analysis and control of dynamical behaviors for coupled reaction-diffusion neural networks. It presents novel research ideas and essential definitions concerning coupled reaction-diffusion neural networks, such as passivity, adaptive coupling, spatial diffusion coupling, and the relationship between synchronization and output strict passivity. Further, it gathers research results previously published in many flagship journals, presenting them in a unified form. As such, the book will be of interest to all university researchers and graduate students in Engineering and Mathematics who wish to study the dynamical behaviors of coupled reaction-diffusion neural networks.
Описание: This book examines the evolvability and robustness of an evolutionary GRN paradigm, in simple differentiated multicellularity and in evolving artificial `organisms` which grow and express an ontogeny from a single cell to a changing neighborhood of cells.
Автор: Godfrey C Onwubolu Название: Hybrid Self-Organizing Modeling Systems ISBN: 3642015298 ISBN-13(EAN): 9783642015298 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Group Method of Data Handling (GMDH) is a typical inductive modeling method that is built on principles of self-organization for modeling complex systems. This book presents hybrids of some computational intelligence techniques and GMDH approach. It includes the description of GAME (Group Adaptive Models Evolution) algorithm.
Автор: Cesare Alippi; Marios M. Polycarpou; Christos Pana Название: Artificial Neural Networks – ICANN 2009 ISBN: 3642042732 ISBN-13(EAN): 9783642042737 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS).
Автор: Godfrey C Onwubolu Название: Hybrid Self-Organizing Modeling Systems ISBN: 3642101828 ISBN-13(EAN): 9783642101823 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Group Method of Data Handling (GMDH) is a typical inductive modeling method that is built on principles of self-organization for modeling complex systems. This book clearly presents hybrids of some computational intelligence techniques and GMDH approach.
Автор: Leonardo Franco; Jos? M. Jerez Название: Constructive Neural Networks ISBN: 3642045111 ISBN-13(EAN): 9783642045110 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constructive neural networks and other incremental learning algorithms are discussed in this volume as alternatives to methods for assessing adequate architectures. A valuable overview of the field is presented, in addition to useful applications.
Автор: Thomas Villmann; Frank-Michael Schleif; Marika Kad Название: Advances in Self-Organizing Maps and Learning Vector Quantization ISBN: 3319076949 ISBN-13(EAN): 9783319076942 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
How Many Dissimilarity/Kernel Self Organizing Map Variants Do We Need.- Dynamic formation of self-organizing maps.- MS-SOM: Magnitude Sensitive Self-Organizing Maps.- Bagged Kernel SOM.- Probability ridges and distortion flows: Visualizing multivariate time series using a variational Bayesian manifold learning method.- Short review of dimensionality reduction methods based on stochastic neighbour embedding.- Attention based Classification Learning in GLVQ and Asymmetric Classification Error Assessment.-Visualization and Classification of DNA sequences using Pareto learning Self Organizing Maps based on Frequency and Correlation Coefficient.- Probabilistic prototype classification using t-norms.- Rejection Strategies for Learning Vector Quantization - a Comparison of Probabilistic and Deterministic Approaches.- Comparison of spectrum cluster analysis with PCA and spherical SOM and related issues not amenable to PCA.- Exploiting the structures of the U-matrix.- Partial Mutual Information for Classification Analysis of Gene expression Data by Learning Vector Quantization.- Composition of Learning Patterns using Spherical Self-Organizing Maps in Image Analysis with Subspace Classifier.- Self-Organizing Map for the Prize-Collecting Traveling Salesman Problem.- A Survey of SOM-based Active Contour Models for Image Segmentation.- Biologically Plausible SOM Representation of the Orthographic Form of 50,000 French Words.- Prototype-based classifiers and their application in the life sciences.- Generative versus discriminative prototype based classification.- Some room for GLVQ: Semantic Labeling of occupancy grid maps.- Anomaly detection based on confidence intervals using SOM with an application to Health Monitoring.- RFSOM - Extending Self-Organizing feature Maps with adaptive metrics to combine spatial and textural features for body pose estimation.- Beyond Standard Metrics - On the Selection and Combination of Distance Metrics for an Improved.- Classification of Hyperspectral Data.- The Sky Is Not the Limit.- Development of Target Reaching Gesture Map in the Cortex and Its Relation to the Motor Map: A Simulation Study.- A Concurrent SOM-based Chan-Vese Model for Image Segmentation.- Text mining of life-philosophicl insights.- SOMbrero: an R Package for Numeric and Non-numeric Self-Organizing Maps.- K-Nearest Neighbor Nonnegative Matrix Factorization for Learning a Mixture of Local SOM Models.
Автор: Eckehard Sch?ll; Sabine H. L. Klapp; Philipp H?vel Название: Control of Self-Organizing Nonlinear Systems ISBN: 3319280279 ISBN-13(EAN): 9783319280271 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Special topics reflecting the active research in the field are the analysis and control of chimera states in classical networks and in quantum systems, the mathematical treatment of multiscale systems, the control of colloidal and quantum transport, the control of epidemics and of neural network dynamics.
Описание: The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs;
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