Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and…mehr
Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling.
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.
Produktdetails
Produktdetails
Advances in Nonlinear Dynamics and Robotics (ANDC)
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).
Inhaltsangabe
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
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