Principles of artificial neural networks [electronic resource] : basic designs to deep learning / Daniel Graupe.
By: Graupe, Daniel
.
Material type: 
Computer fileSeries: Advanced series in circuits and systems ; v. 8.Publisher: Singapore : World Scientific Publishing Co. Pte Ltd., ©2019Edition: 4th ed.Description: 1 online resource (440 p.) : ill.ISBN: 9789811201233.Subject(s): Neural networks (Computer science)Genre/Form: Electronic books.DDC classification: 006.3/2 Online resources: Access to full text is restricted to subscribers. Summary: "The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning. This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks - demonstrating how such case studies are designed, executed and how their results are obtained. The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining."-- Publisher's website.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Title from web page (viewed April 9, 2019).
Includes bibliographical references and indexes.
"The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning. This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks - demonstrating how such case studies are designed, executed and how their results are obtained. The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining."-- Publisher's website.
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