Multilayer feedforward networks are universal approximators
Neural Networks
Proceedings of the international workshop on Artificial neural networks
IWANN '91 Proceedings of the international workshop on Artificial neural networks
IWANN '93 Proceedings of the International Workshop on Artificial Neural Networks: New Trends in Neural Computation
IWANN '96 Proceedings of the International Workshop on Artificial Neural Networks: From Natural to Artificial Neural Computation
IWANN '97 Proceedings of the International Work-Conference on Artificial and Natural Neural Networks: Biological and Artificial Computation: From Neuroscience to Technology
IWANN '99 Proceedings of the International Work-Conference on Artificial and Natural Neural Networks: Foundations and Tools for Neural Modeling
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Computational Intelligence and Bioinspired Systems: 8th International Work-Conference on Artificial Neural Networks, IWANN 2005, Vilanova i la Geltrú, ... (Lecture Notes in Computer Science)
Artificial Neural Nets. Problem Solving Methods: 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, Maó, Menorca, ... Part II (Lecture Notes in Computer Science)
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Editorial: Computational and ambient intelligence
Neurocomputing
Advances in Computational Intelligence: 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, Torremolinos-Mlaga, Spain, June ... Computer Science and General Issues)
Machine Learning: A Probabilistic Perspective
Machine Learning: A Probabilistic Perspective
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This work aims at a reflection on the evolution of the field of Neurocomputing along the last 20 years that have witnessed the sequence of editions of the International Work-Conference on Artificial Neural Networks (IWANN). This reflection arises inextricably of the evolution of connectionist networks themselves, describing their features and most remarkable particularities, most of which have prevailed in time. Another trend that is worth mentioning is the development of a strong interconnection with other paradigms comprised under the so-called Computational Intelligence, which can be understood as a set of nature-inspired computational methodologies and approaches to address complex real-world problems, which traditional approaches are ineffective or unfeasible to deal with. Indeed, many hybrid computational intelligence schemes have been developed that efficiently combine procedures from the domains of artificial neural networks, machine learning, evolutionary computation and fuzzy logic to be applied in complex domains. Finally, a brief description of the diverse contributions that have been included in this special issue is presented. These papers stem from previous versions presented at IWANN2011.