Sign up
Forgot password?
FAQ: Login

Kozma R., Alippi C., Choe Y., Morabito F. (Eds.) Artificial Intelligence in the Age of Neural Networks and Brain Computing

  • pdf file
  • size 30,67 MB
Kozma R., Alippi C., Choe Y., Morabito F. (Eds.) Artificial Intelligence in the Age of Neural Networks and Brain Computing
2nd Edition. — Academic Press, 2023. — 400 p. — eBook ISBN: 9780323958165.
Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI are a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massively parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework for deep learning, and launches novel and intriguing paradigms as possible future alternatives.
The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters.
Key features
Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN).
Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control, and decision-making.
Edited by high-level academics and researchers in intelligent systems and neural networks.
Includes all-new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks.
True PDF
  • Sign up or login using form at top of the page to download this file.
  • Sign up
Up