Constructive neural networks
The book is a collection of invited papers on Constructive methods for Neural networks. Most of the chapters are extended versions of works presented on the special session on constructive neural network algorithms of the 18th International Conference on Artificial Neural Networks (ICANN 2008) held...
Guardat en:
| Autor principal: | |
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| Altres autors: | , |
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2009.
Cham : Springer Nature |
| Col·lecció: | Studies in Computational Intelligence
258 |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Constructive Neural Networks, Texte imprimé, 9783642045110 • Constructive Neural Networks, Texte imprimé, 9783642045288 • Constructive Neural Networks, Texte imprimé, 9783642261084 |
Taula de continguts:
- Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks
- Efficient Constructive Techniques for Training Switching Neural Networks
- Constructive Neural Network Algorithms That Solve Highly Non-separable Problems
- On Constructing Threshold Networks for Pattern Classification
- Self-Optimizing Neural Network 3
- M-CLANN: Multiclass Concept Lattice-Based Artificial Neural Network
- Constructive Morphological Neural Networks: Some Theoretical Aspects and Experimental Results in Classification
- A Feedforward Constructive Neural Network Algorithm for Multiclass Tasks Based on Linear Separability
- Analysis and Testing of the m-Class RDP Neural Network
- Active Learning Using a Constructive Neural Network Algorithm
- Incorporating Expert Advice into Reinforcement Learning Using Constructive Neural Networks
- A Constructive Neural Network for Evolving a Machine Controller in Real-Time
- Avoiding Prototype Proliferation in Incremental Vector Quantization of Large Heterogeneous Datasets
- Tuning Parameters in Fuzzy Growing Hierarchical Self-Organizing Networks
- Self-Organizing Neural Grove: Efficient Multiple Classifier System with Pruned Self-Generating Neural Trees.