02338nam 2200409 450 991068338650332120230702134818.03-0365-6689-910.3390/books978-3-0365-6689-4(CKB)5700000000354365(NjHacI)995700000000354365(EXLCZ)99570000000035436520230702d2023 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierMemristive Devices and Systems Modelling, Properties & Applications /Chun Sing Lai, Zhekang Dong, Donglian Qi, editorsBasel :MDPI - Multidisciplinary Digital Publishing Institute,2023.1 online resource (218 pages)3-0365-6688-0 Includes bibliographical references.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.Memristive Devices and SystemsElectronicsElectronics.621.381Lai Chun SingDong ZhekangQi DonglianNjHacINjHaclBOOK9910683386503321Memristive Devices and Systems3394721UNINA