Principles of artificial neural networks
Material type: TextSeries: Advanced series on circuits and systems ; vol 8Publication details: Singapore world scientific 2020Edition: 3rd editionDescription: xviii, 363 pISBN: 9789814522731 (hbk)Subject(s): Neural networks (Computer science)DDC classification: 006.32 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.Item type | Current library | Call number | Status | Date due | Barcode |
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BK | Stack | 006.32 GRA/P (Browse shelf (Opens below)) | Available | 54422 |
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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.
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