347,30 €
385,89 €
-10% with code: EXTRA
Neural Networks: Computational Models and Applications
Neural Networks: Computational Models and Applications
347,30
385,89 €
  • We will send in 10–14 business days.
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, insightfu…
385.89
  • Publisher:
  • ISBN-10: 3540692258
  • ISBN-13: 9783540692256
  • Format: 16.3 x 23.6 x 1.8 cm, kieti viršeliai
  • Language: English
  • SAVE -10% with code: EXTRA

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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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  • Author: Huajin Tang
  • Publisher:
  • ISBN-10: 3540692258
  • ISBN-13: 9783540692256
  • Format: 16.3 x 23.6 x 1.8 cm, kieti viršeliai
  • Language: English English

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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