• Produktbild: Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications
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Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.07.2021

Herausgeber

Christos Volos + weitere

Verlag

Elsevier Science & Technology

Seitenzahl

570

Maße (L/B/H)

22,9/15,2/2,9 cm

Gewicht

754 g

Sprache

Englisch

ISBN

978-0-12-821184-7

Beschreibung

Portrait

Christos Volos received the Physics Diploma degree, the M.Sc. degree in electronics, and the Ph.D. degree in chaotic electronics from the Physics Department, Aristotle University of Thessaloniki, in 1999, 2002, and 2008, respectively. He is currently an Associate Professor with the Physics Department, Aristotle University of Thessaloniki, Greece and a member of the Laboratory of Nonlinear Circuits - Systems & Complexity (LaNSCom).Viet-Thanh Pham is the Director of Research at Faculty of Electrical and Electronic Engineering, Phenikaa Institute for Advanced Study (PIAS), Phenikaa University, Vietnam. He received the degree in electronics and telecommunications from the Hanoi University of Technology, Vietnam, in 2005, and the Ph.D. degree in electronics, automation and control of complex systems engineering from the University of Catania, Italy, in 2013. He was a postdoctoral researcher at the Division of Dynamics, Lodz University of Technology, Poland.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.07.2021

Herausgeber

Verlag

Elsevier Science & Technology

Seitenzahl

570

Maße (L/B/H)

22,9/15,2/2,9 cm

Gewicht

754 g

Sprache

Englisch

ISBN

978-0-12-821184-7

EU-Ansprechpartner

Zeitfracht Medien GmbH
Ferdinand-Jühlke-Straße 7
99095 Erfurt
DE
produktsicherheit@zeitfracht.de

Herstelleradresse

Elsevier Science & Technology
125 London Wall
EC2Y 5AS London
GB
tradeorders@elsevier.com

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  • Produktbild: Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications
  • Produktbild: Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications
  • Part I: Mem-elements and their emulators

    1. The fourth circuit element was found: a brief history
    2. Implementing memristor emulators in hardware
    3. On the FPGA implementation of chaotic oscillators based on memristive circuits
    4. Microwave memristive components for smart RF front-end modules
    5. The modeling of memcapacitor oscillator motion with ANN and its nonlinear control application
    6. Rich dynamics of memristor based Liénard systems
    7. Hidden extreme multistability generated from a novel memristive two-scroll chaotic system
    8. Extreme multistability, hidden chaotic attractors and amplitude controls in an absolute memristor Van der Pol-Duffing circuit: dynamical analysis and electronic implementation
    9. Memristor-based novel 4D chaotic system without equilibria
    10. Memristor Helmholtz oscillator: analysis, electronic implementation, synchronization and chaos control using single controller
    11. Design guidelines for physical implementation of fractional-order integrators and its application in memristive systems
    12. Control of bursting oscillations in memristor based Wien-bridge oscillator

    Part II: Applications of mem-elements

    13. Memristor, mem-systems and neuromorphic applications: a review
    14. Guidelines for benchmarking non-ideal analog memristive crossbars for neural networks
    15. Bipolar resistive switching in biomaterials: case studies of DNA and melanin-based bio-memristive devices
    16. Nonvolatile memristive logic: a road to in-memory computing
    17. Implementation of organic RRAM with ink-jet printer: from design to using in RFID-based application
    18. Neuromorphic vision networks for face recognition
    19. Synaptic devices based on HfO2 memristors
    20. Analog circuit integration of backpropagation learning in memristive HTM architecture
    21. Multi-stable patterns coexisting in memristor synapse-coupled Hopfield neural network
    22. Fuzzy memristive networks
    23. Fuzzy integral sliding mode technique for synchronization of memristive neural networks
    24. Robust adaptive control of fractional-order memristive neural networks
    25. Learning memristive spiking neurons and beyond