Neural Networks: Computational Models and Applications
Book information
Description
Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. The book offers a compact, insightful understanding of the broad and rapidly growing neural networks domain.
Similar books
Neural Networks Computational Models and Applications
2007 · PDF
Neuromorphic Cognitive Systems. A Learning and Memory centered Approach
2017 · PDF
Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)
Intelligent Analysis of Fundus Images. Methods and Applications
2023 · PDF
Evolutionary Multi-Task Optimization: Foundations and Methodologies
2023 · PDF
Advances in Neural Networks – ISNN 2019: 16th International Symposium on Neural Networks, ISNN 2019, Moscow, Russia, July 10–12, 2019, Proceedings, Part II
2019 · PDF
Advances in Neural Networks – ISNN 2019: 16th International Symposium on Neural Networks, ISNN 2019, Moscow, Russia, July 10–12, 2019, Proceedings, Part I
2019 · PDF
Evolutionary Computation and Complex Networks
2019 · PDF