Memristive Devices and Systems: Modelling, Properties & Applications

Edited by
February 2023
218 pages
  • ISBN978-3-0365-6688-7 (Hardback)
  • ISBN978-3-0365-6689-4 (PDF)

This book is a reprint of the Special Issue Memristive Devices and Systems: Modelling, Properties & Applications that was published in

Computer Science & Mathematics
Physical Sciences

This reprint presents the Special Issue on “Memristive Devices and Systems: Modeling, Properties, and Applications”. The Special Issue provides a comprehensive overview of key computational primitives enabled by these memory devices, as well as their applications, spanning edge computing, signal processing, optimization, machine learning, deep learning, stochastic computing, and so on. The memristor is considered to be a promising candidate for next-generation computing systems due to its nonvolatility, high density, low power, nanoscale geometry, nonlinearity, binary/multiple memory capacity, and negative differential resistance. Novel computing architectures/systems based on memristors have shown great potential to replace the traditional von Neumann computing architecture, which faces data movement challenges. With the development of material science, novel preparation and modeling methods for different memristive devices have been put forward recently, which opens up a new path for realizing different computing systems/architectures with practical memristor properties.

  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
memristor; history erase effect; dynamic route; power-off plot; RRAM; 1T-1R; multilevel; compact modeling; Verilog-A; artificial neural network; chaos; fractional-order calculus; memristor model; coexisting attractors; Adomian decomposition method; VO2 carbon nanotube composite memristor; cellular neural network (CNN); von Neumann structure; local activity; edge of chaos; emulator; gyrator; memcapacitor; meminductor; memristor; memristors; memristive systems; integrated storage and computation; image processing; memristor; chaos; local activity; the edge of chaos; memristor; local activity; chaos; memristor; Hopfield neural network; chaos; synaptic crosstalk; coexisting dynamics; optoelectronic memristor; composite circuit; multi-valued logic; rotation mechanism; n/a