{
"item_title" : "Neural Networks",
"item_author" : [" Huajin Tang", "Kay Chen Tan", "Zhang Yi "],
"item_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.",
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Neural Networks : Computational Models and Applications
Overview
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.
This item is Non-Returnable
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Details
- ISBN-13: 9783540692256
- ISBN-10: 3540692258
- Publisher: Springer
- Publish Date: March 2007
- Dimensions: 9.3 x 6.4 x 0.7 inches
- Shipping Weight: 1.2 pounds
- Page Count: 300
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