Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications: Advances in Nonlinear Dynamical Systems and Robotics (ANDC)
Editat de Christos Volos, Viet-Thanh Phamen Limba Engleză Paperback – 25 iun 2021
As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields.
- Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence
- Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor)
- Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence
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Specificații
ISBN-13: 9780128211847
ISBN-10: 0128211849
Pagini: 568
Ilustrații: Approx. 200 illustrations
Dimensiuni: 152 x 229 mm
Greutate: 0.75 kg
Editura: ELSEVIER SCIENCE
Seria Advances in Nonlinear Dynamical Systems and Robotics (ANDC)
ISBN-10: 0128211849
Pagini: 568
Ilustrații: Approx. 200 illustrations
Dimensiuni: 152 x 229 mm
Greutate: 0.75 kg
Editura: ELSEVIER SCIENCE
Seria Advances in Nonlinear Dynamical Systems and Robotics (ANDC)
Public țintă
Researchers from academia and industry, who are working in the research areas—dynamical systems, artificial intelligence, electrical engineering, computer science, information technology and neuromorphic systems .Graduate or advanced undergraduate level as a textbook or major reference for courses such as electrical circuits, nonlinear dynamical systems, mathematical modelling, computational science, numerical simulation, and many others.
Graduate students and young researchers in the following fields: Biomedical Engineering; Computational biology; Computer science; Computational Physics; Engineering Mathematics, Electrical and Electronic Engineering; Mathematics; Physics.
Cuprins
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
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