Memristor and memristive neural networks

• Autore: Alex Pappachen James
• Pubblicazione: IntechOpen, 2018; [Place of publication not identified] : , : IntechOpen, , 2018; ©2018
• Descrizione fisica: 1 online resource (328 pages)
• Disciplina: 006
• Soggetto topico: COMPUTERS / Data Science / Neural Networks
• Soggetto non controllato: Physical Sciences; Engineering and Technology; Neural Network; Computer and Information Science; Numerical Analysis and Scientific Computing
• Persona (resp. second.): JamesAlex Pappachen
• Sommario/riassunto: This book covers a range of models, circuits and systems built with memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications. The resistive switching property is an important aspect of the memristors, and there are several designs of this discussed in this book, such as in metal oxide/organic semiconductor nonvolatile memories, nanoscale switching and degradation of resistive random access memory and graphene oxide-based memristor. The modelling of the memristors is required to ensure that the devices can be put to use and improve emerging application. In this book, various memristor models are discussed, from a mathematical framework to implementations in SPICE and verilog, that will be useful for the practitioners and researchers to get a grounding on the topic. The applications of the memristor models in various neuromorphic networks are discussed covering various neural network models, implementations in A/D converter and hierarchical temporal memories.
• Titolo autorizzato: Memristor and memristive neural networks
• ISBN: 953-51-4009-4; 953-51-3948-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910317826903321
• Lo trovi qui: Univ. Federico II