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Tuesday, October 20

An Introduction to Neural Networks

An Introduction to Neural Networks

Though mathematical ideas underpin the study of neural networks, the author presents the mathematical foundations without the apparatus. All aspects of the field are addressed, including the artificial neurons as models of their real counterparts, the geometry of the Action Network in the pattern space, the gradient descent methods, including copies of propagation and  associative memory networks Hopfield, and self-organization and feature maps. The traditionally difficult subject of the theory of adaptive resonance is clarified in a hierarchical description of its operation. The book also includes several real-world examples to provide a practical approach. This should enhance its appeal to those involved in the design, construction and management of
networks in business environments and who want to improve their understanding of the network simulator packages. As a general introduction and easy access to one of the most important issues in cognitive science and computer science, this volume should interest a wide range of readers, students and professionals in cognitive science, psychology, computer science and electrical engineering.

An Introduction to Neural Networks (ebook-Math-Computer Science).pdf

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