Adamatzky / Chua / Sirakoulis

Handbook of Memristor Networks

Jetzt vorbestellen!
1st ed. 2019. Buch. Bibliographien. Hardcover
Springer ISBN 978-3-319-76374-3
Format (B x L): 15,5 x 23,5 cm
In englischer Sprache
A memristor is a two-terminal device whose resistance depends on one or more internal state variables of the device and it is defined by a state-dependent Ohm's law. Its resistance depends on the entire past signal waveform of the applied voltage, or current, across the memristor. Using memristors one can achieve circuit functionalities that are not possible to establish with resistors, capacitors and inductors, therefore the memristor is of great pragmatic usefulness.
Potential unique applications of memristors are in spintronic devices, ultra-dense information storage, neuromorphic circuits, and programmable electronics. This handbook focuses on design, fabrication, modelling of and implementation of computation in spatially extended discrete media with many memristors. The World's authorities in computer science, mathematics, electronics, physics and computer engineering present:

- foundations of the memristor theory and applications
- demonstrate how to design neuromorphic network architectures based on memristor assemblies
- analysis varieties of the dynamic behaviour of memristive networks
- show how to realise computing devices from memristors

The Handbook of Memristor Networks is a unique self-contained compendium of results on memristor research developed by top world experts in the field. All aspects of memristor networks are presented in detail, in a fully accessible, often tutorial like style. The book is an indispensable source of information and an inspiring reference text for future generations of computer scientists, mathematicians, physicists and engineers.
vorbestellbar, wir liefern bei Erscheinen

Erscheint vsl. im November 2018

330,63 €
inkl. MwSt.
Covers all aspects of memristor networks in detail Explains how to realise computing devices from memristors Presents the latest developments in the field of memristor networks