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Handbook of Memristor Networks (Repost)

Posted By: AvaxGenius
Handbook of Memristor Networks (Repost)

Handbook of Memristor Networks by Leon Chua
English | EPUB | 2019 | 1357 Pages | ISBN : 3319763741 | 262.4 MB

This Handbook presents all aspects of memristor networks in an easy to read and tutorial style. Including many colour illustrations, it covers the foundations of memristor theory and applications, the technology of memristive devices, revised models of the Hodgkin-Huxley Equations and ion channels, neuromorphic architectures, and analyses of the dynamic behaviour of memristive networks. It also shows how to realise computing devices, non-von Neumann architectures and provides future building blocks for deep learning hardware.

Handbook of Memristor Networks (Repost)

Posted By: AvaxGenius
Handbook of Memristor Networks (Repost)

Handbook of Memristor Networks by Leon Chua
English | EPUB | 2019 | 1357 Pages | ISBN : 3319763741 | 262.4 MB

This Handbook presents all aspects of memristor networks in an easy to read and tutorial style. Including many colour illustrations, it covers the foundations of memristor theory and applications, the technology of memristive devices, revised models of the Hodgkin-Huxley Equations and ion channels, neuromorphic architectures, and analyses of the dynamic behaviour of memristive networks. It also shows how to realise computing devices, non-von Neumann architectures and provides future building blocks for deep learning hardware.

Handbook of Memristor Networks (Repost)

Posted By: AvaxGenius
Handbook of Memristor Networks (Repost)

Handbook of Memristor Networks by Leon Chua
English | EPUB | 2019 | 1357 Pages | ISBN : 3319763741 | 262.4 MB

This Handbook presents all aspects of memristor networks in an easy to read and tutorial style. Including many colour illustrations, it covers the foundations of memristor theory and applications, the technology of memristive devices, revised models of the Hodgkin-Huxley Equations and ion channels, neuromorphic architectures, and analyses of the dynamic behaviour of memristive networks. It also shows how to realise computing devices, non-von Neumann architectures and provides future building blocks for deep learning hardware.