Springer - Artificial Neural Networks: A Practical Course (2017 EN)

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    Author: Ivan Nunes da Silva, Danilo Hernane Spatti, Rogerio Andrade Flauzino, Luisa Helena Bartocci Liboni, Silas Franco dos Reis Alves
    Full Title: Artificial Neural Networks: A Practical Course
    Publisher: Springer; 1st ed. 2017 edition (August 24, 2016)
    Year: 2017
    ISBN-13: 9783319431628 (978-3-319-43162-8), 9783319431611 (978-3-319-43161-1)
    ISBN-10: 3319431625, 3319431617
    Pages: 307
    Language: English
    Genre: Engineering: Signals & Communication; Computational Intelligence; Data Mining and Knowledge Discovery
    File type: PDF (True)
    Quality: 10/10
    Price: 88.39 €


    This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.

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