Suchergebnisse - "Memristive Devices for Neuromorphic Computing"

Review of Ti3C2Tx MXene Nanofluids: Synthesis, Characterization, and Applications

Autoren: Ilancheliyan Samylingam K. Kadirgama L. Samylingam et al.

Quelle: Engineering, Technology & Applied Science Research. 14:14708-14712

Schlagwörter: Memristive Devices for Neuromorphic Computing, Two-Dimensional Transition Metal Carbides and Nitrides (MXenes), Materials Science, 0211 other engineering and technologies, 02 engineering and technology, Nanofluid, TA401-492 Materials of engineering and construction. Mechanics of materials, 7. Clean energy, MXenes, Engineering, Nanoparticle, Nanosheets, Materials Chemistry, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Nanotechnology, Electrical and Electronic Engineering, Two-Dimensional Materials, FOS: Nanotechnology, 9. Industry and infrastructure, Materials science, 3. Good health, Physical Sciences, 8. Economic growth, Characterization (materials science)

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Fabrication of new Mn-based MXene structure from MnO2 for electrochemical energy storage applications

Autoren: Mostafa S. Eraky Mohamed H. El-Sadek Atef Y. Shenouda et al.

Quelle: Monatshefte für Chemie - Chemical Monthly. 155:289-297

Schlagwörter: Alternative medicine, Energy storage, Memristive Devices for Neuromorphic Computing, Electrode, Two-Dimensional Transition Metal Carbides and Nitrides (MXenes), Materials Science, 02 engineering and technology, 01 natural sciences, Quantum mechanics, 7. Clean energy, Fabrication, Engineering, Materials Chemistry, FOS: Electrical engineering, electronic engineering, information engineering, Electrochemistry, Pathology, Nanotechnology, Electrical and Electronic Engineering, Two-Dimensional Materials, FOS: Nanotechnology, Supercapacitor, Physics, Power (physics), Materials science, 6. Clean water, 0104 chemical sciences, Chemistry, Physical chemistry, Physical Sciences, Medicine, Electrochemical energy storage, 0210 nano-technology

A Virtual Fabrication and High-Performance Design of 65 nm Nanocrystal Floating-Gate Transistor

Autoren: Thinh Dang Cong Trang Hoang

Quelle: Modelling and Simulation in Engineering, Vol 2024 (2024)

Schlagwörter: Alternative medicine, Ferroelectric Devices for Low-Power Nanoscale Applications, Memristive Devices for Neuromorphic Computing, Nanocrystal, 7. Clean energy, Resistive Switching, Fabrication, Layer (electronics), Engineering, Thin-film transistor, FOS: Electrical engineering, electronic engineering, information engineering, Pathology, Nanotechnology, Electrical and Electronic Engineering, Optoelectronics, FOS: Nanotechnology, Transistor, Voltage, QA75.5-76.95, Materials science, Electronic computers. Computer science, Atomic Layer Deposition Technology, Electrical engineering, Physical Sciences, Metal Gate Transistors, Medicine, Non-Volatile Memory

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Zugangs-URL: https://doaj.org/article/2c02fcfefce049d5ae8f1fefa3ee6f4a

CalyPSO: An Enhanced Search Optimization based Framework to Model Delay-based PUFs

Autoren: Nimish Mishra Kuheli Pratihar Sekhar Mandal et al.

Quelle: Transactions on Cryptographic Hardware and Embedded Systems, Vol 2024, Iss 1 (2023)

Schlagwörter: Computer engineering. Computer hardware, Artificial intelligence, Physically Unclonable Functions, Memristive Devices for Neuromorphic Computing, Robustness (evolution), Variety (cybernetics), Failure Analysis of Integrated Circuits, Information technology, Modeling Attacks, Biochemistry, Gene, TK7885-7895, Hardware Security and Authentication Techniques, Engineering, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, PUF-Based Authentication, Particle swarm optimization, T58.5-58.64, Computer science, Algorithm, Chemistry, Genetic algorithm, Particle Swarm Optimization, Hardware and Architecture, Computer Science, Physical Sciences, Physical Unclonable Functions, Cryptography, Evolutionary Algorithms

Zugangs-URL: https://doaj.org/article/33bfd8d8ae3244cc85c3a270ad328efc

Spinel ferrites for resistive random access memory applications

Autoren: Ketankumar Gayakvad Kaushik Somdatta V. L. Mathe et al.

Quelle: Emergent Materials. 7:103-131

Schlagwörter: Non-blocking I/O, Composite material, Ferrite (magnet), Memristive Devices for Neuromorphic Computing, Ferroelectric Devices for Low-Power Nanoscale Applications, Materials Science, Spinel, Resistive random-access memory, 02 engineering and technology, Biochemistry, 01 natural sciences, 7. Clean energy, Resistive Switching, Catalysis, Engineering, 0103 physical sciences, FOS: Electrical engineering, electronic engineering, information engineering, Materials Chemistry, Doping, Electrical and Electronic Engineering, Optoelectronics, Voltage, Memory Applications, Materials science, Chemistry, Electrical engineering, Physical Sciences, Metallurgy, Lead-free Piezoelectric Materials, Non-Volatile Memory, 0210 nano-technology

Different Methods of EEG Signal Analysis Using Power Spectral Density, ChronoNet and ResNest

Autoren: Md. Mehedi Hasan Senjuti Rahman Ajay Krishno Sarkar et al.

Quelle: European Journal of Electrical Engineering and Computer Science. 7:20-27

Schlagwörter: Blind Source Separation and Independent Component Analysis, Artificial intelligence, Support vector machine, Cognitive Neuroscience, Memristive Devices for Neuromorphic Computing, 02 engineering and technology, Pattern recognition (psychology), Bayesian probability, Epilepsy Detection, EEG Analysis, Bayes' theorem, 03 medical and health sciences, Engineering, Spectral density, 0302 clinical medicine, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Decision tree, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Psychology, Deep Learning for EEG, Electrical and Electronic Engineering, Epilepsy, Naive Bayes classifier, 4. Education, Life Sciences, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, 16. Peace & justice, Computer science, 3. Good health, FOS: Psychology, Neural Ensemble Physiology, Combinatorics, Physical Sciences, Signal Processing, Computer Science, Kernel (algebra), Telecommunications, Feature extraction, Mathematics, Neuroscience, Random forest

Segment-Aware Dynamic Partitioning PCM-DRAM: A Solution to IoT Devices Development Constraints

Autoren: Qingyang Zhu Liu Shu-yi Zahid Akhtar et al.

Quelle: Journal of Computer Science. 19:1212-1221

Schlagwörter: Computer Networks and Communications, Memristive Devices for Neuromorphic Computing, Internet of Things, Dynamic random-access memory, 7. Clean energy, Dram, Engineering, FOS: Electrical engineering, electronic engineering, information engineering, Parallel Computing and Performance Optimization, Electrical and Electronic Engineering, Phase change, Embedded system, Content-Centric Networking for Information Delivery, Phase-change memory, Computer network, Performance Optimization, Computer hardware, Engineering physics, Computer science, Distributed computing, Energy consumption, Semiconductor memory, Hardware and Architecture, Electrical engineering, Physical Sciences, Computer Science

VLSI Implementation of Hybrid Memristor Based Logic Gates

Autoren: Ritesh Samanta Namburi VamsiKrishna Poongundran Selvaprabhu et al.

Quelle: International Journal of Electrical and Electronics Research. 11:733-737

Schlagwörter: Memristive Devices for Neuromorphic Computing, Electronic circuit, 02 engineering and technology, 7. Clean energy, Resistive Switching, PMOS logic, Cellular and Molecular Neuroscience, Engineering, Pass transistor logic, CMOS Image Sensor Technology, CMOS Image Sensors, FOS: Electrical engineering, electronic engineering, information engineering, Resistor, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Breadboard, Electronic engineering, CMOS, Transistor, Life Sciences, Logic gate, Voltage, Neural Interface Technology, Capacitor, Memristor, Digital electronics, Computer science, Electrical engineering, Physical Sciences, 0210 nano-technology, NMOS logic, Neuroscience

Sailboat navigation control system based on spiking neural networks

Autoren: Nelson Giraldo Sebastián Isaza Ricardo Velasquez

Quelle: Control Theory and Technology. 21:489-504

Schlagwörter: Artificial neural network, Artificial intelligence, Photonic Reservoir Computing for Neural Computation, Memristive Devices for Neuromorphic Computing, Cognitive Neuroscience, Control (management), 02 engineering and technology, Mathematical analysis, 7. Clean energy, Systems engineering, 03 medical and health sciences, Task (project management), 0302 clinical medicine, Engineering, Spiking Neurons, Artificial Intelligence, Spiking neural network, Reinforcement learning, 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 14. Life underwater, Electrical and Electronic Engineering, Brain-inspired Computing, Control system, Neuronal Oscillations in Cortical Networks, Biology, Scheme (mathematics), Computational intelligence, Software engineering, Control engineering, Controller (irrigation), Life Sciences, Computer science, Agronomy, Electrical engineering, Physical Sciences, Computer Science, Spike (software development), Simulation, Mathematics, Neuroscience

A Lightweight Mitigation Technique for Resource- Constrained Devices Executing DNN Inference Models Under Neutron Radiation

Autoren: Jonas Gava Alex Hanneman Geancarlo Abich et al.

Weitere Verfasser: Jonas Gava Alex Hanneman Geancarlo Abich et al.

Quelle: RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)

Schlagwörter: Artificial neural network, Artificial intelligence, Memristive Devices for Neuromorphic Computing, Convolutional neural network, Neutron Radiation, Real-time computing, Engineering, Error Detection, DNN and CNN inference models, Inference, Computer engineering, FOS: Electrical engineering, electronic engineering, information engineering, [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, Arm Cortex-M, Electrical and Electronic Engineering, Resource allocation, Embedded system, Neuromorphic Computing, Computer network, DNN and CNN inference model, resource-constrained device, Computer science, Overhead (engineering), Operating system, PACS 8542, Fault Tolerance in Electronic Systems, neutron radiation, Atomic Layer Deposition Technology, Resource-constrained Devices, Physical Sciences, Soft Errors, Software, Simulation

Zugangs-URL: http://hdl.handle.net/10045/133418
https://hdl.handle.net/10045/133418

Effects of logic glitch and (area-power dissipation) leakage on cryptosystems using clock gating technique to enhance web etiquette

Autoren: Akhigbe-mudu Thursday Ehis

Quelle: Brazilian Journal of Science. 2:38-52

Schlagwörter: Energy Efficiency, Memristive Devices for Neuromorphic Computing, Subthreshold conduction, 02 engineering and technology, 01 natural sciences, 7. Clean energy, Engineering, Power Management, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Parallel Computing and Performance Optimization, 0101 mathematics, Electrical and Electronic Engineering, Embedded system, Electronic engineering, CMOS, Transistor, Voltage, Low-Power VLSI Circuit Design and Optimization, Computer science, Leakage Reduction, Programming language, Energy consumption, Low-Power, Hardware and Architecture, Electrical engineering, Physical Sciences, Computer Science, Software portability, Glitch

Towards Improving Motor Imagery Brain–Computer Interface Using Multimodal Speech Imagery

Autoren: Jigang Tong Zhengxing Xing Xiaoying Wei et al.

Quelle: Journal of Medical and Biological Engineering. 43:216-226

Schlagwörter: Parallel computing, Interface (matter), Artificial intelligence, Pronunciation, Pinyin, Cognitive Neuroscience, Memristive Devices for Neuromorphic Computing, 0206 medical engineering, 02 engineering and technology, Speech recognition, 7. Clean energy, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Engineering, Motor imagery, Reading (process), FOS: Electrical engineering, electronic engineering, information engineering, Psychology, Electrical and Electronic Engineering, Brain-inspired Computing, Neuromorphic Computing, Bubble, Life Sciences, Electroencephalography, Linguistics, Neural Interface Technology, Brain-Computer Interfaces in Neuroscience and Medicine, 16. Peace & justice, Computer science, Chinese characters, BCI Technology, FOS: Philosophy, ethics and religion, Brain–computer interface, FOS: Psychology, Philosophy, Brain-Computer Interfaces, Physical Sciences, FOS: Languages and literature, Motor Imagery, Maximum bubble pressure method, Neuroscience

Network Intelligence for NFV Scaling in Closed-Loop Architectures

Autoren: Paola Soto Miguel Camelo Danny De Vleeschauwer et al.

Quelle: IEEE communications magazine
IEEE Communications Magazine

Schlagwörter: Artificial intelligence, Computer Networks and Communications, Memristive Devices for Neuromorphic Computing, FOS: Mechanical engineering, Zero-Touch Networks, Visual arts, Automation, Engineering, Computer security, Reinforcement learning, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Self-Adaptive Systems, Cloud computing, Electrical and Electronic Engineering, Brain-inspired Computing, Key (lock), NFV scaling, Computer. Automation, Management and Orchestration, Adaptation (eye), Machine Learning for Networking, Physics, Orchestration, Software-Defined Networking and Network Virtualization, Optics, Network Automation, Security Challenges in Smart Grid Systems, Computer science, Reinforcement Learning, Software-Defined Networking, Distributed computing, Mechanical engineering, Operating system, Control and Systems Engineering, Computer Science, Physical Sciences, Mass communications, Musical, Art

Zugangs-URL: https://repository.uantwerpen.be/docstore/d:irua:19095
https://hdl.handle.net/10067/1984940151162165141

Energy efficient IPC based dual compression for endurance enhancement of NVRAM as main memory in embedded devices

Autoren: Sakthivel Palanivelu Saravana Kumar Radhakrishnan C. Kumar et al.

Quelle: IET Communications, Vol 17, Iss 11, Pp 1310-1320 (2023)

Schlagwörter: Computer Networks and Communications, Memristive Devices for Neuromorphic Computing, TK5101-6720, Workload, 02 engineering and technology, Latency (audio), 7. Clean energy, Resistive Switching, Memory refresh, Engineering, Parallel Computing and Performance Optimization, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, GPU Computing, Electrical and Electronic Engineering, Embedded system, energy conservation, Non-volatile random-access memory, Performance Optimization, Computer hardware, Computer science, Operating system, pattern matching, Non-volatile memory, Semiconductor memory, Hardware and Architecture, Distributed Storage Systems and Network Coding, Computer Science, Physical Sciences, Telecommunication, NAND Flash Memory, Telecommunications, Non-Volatile Memory, Computer memory

Zugangs-URL: https://doaj.org/article/3f36d81d0b93492db1e05fede3aa588c

Propofol Reversibly Attenuates Short-Range Microstate Ordering and 20 Hz Microstate Oscillations

Autoren: Gesine Hermann Inken Tödt Enzo Tagliazucchi et al.

Quelle: Brain Topography. 37:329-342

Schlagwörter: Artificial intelligence, Cognitive Neuroscience, Memristive Devices for Neuromorphic Computing, Quantum mechanics, EEG Analysis, Engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Humans, Cluster Analysis, Ministate, Entropy (arrow of time), Psychology, Electrical and Electronic Engineering, Propofol, Neuronal Oscillations in Cortical Networks, Physics, Brain, Life Sciences, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, FOS: Psychology, Alpha Rhythm, Physical Sciences, Statistical physics, Mathematics, Neuroscience

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38228923

3D Printing of MXenes-Based Electrodes for Energy Storage Applications

Autoren: G Aadharshini Nisha Gupta Prosenjit Saha et al.

Quelle: Recent Progress in Materials. :1-23

Schlagwörter: Renewable energy, Electrochemical Properties, Energy storage, batteries, Memristive Devices for Neuromorphic Computing, Electrode, Two-Dimensional Transition Metal Carbides and Nitrides (MXenes), Materials Science, Wearable Nanogenerator Technology, Biomedical Engineering, FOS: Mechanical engineering, Capacitance, 02 engineering and technology, FOS: Medical engineering, 01 natural sciences, Quantum mechanics, 7. Clean energy, MXenes, Engineering, Energy Harvesting, Materials Chemistry, FOS: Electrical engineering, electronic engineering, information engineering, Nanotechnology, Electrical and Electronic Engineering, Two-Dimensional Materials, Supercapacitor, FOS: Nanotechnology, Physics, 3D printing, Energy Storage, Power (physics), Computer science, Materials science, Mechanical engineering, 0104 chemical sciences, Chemistry, Physical chemistry, 13. Climate action, Electrical engineering, Physical Sciences, Process engineering, 0210 nano-technology

A Systematic Review of Using Deep Learning Technology in the Steady-State Visually Evoked Potential-Based Brain-Computer Interface Applications: Current Trends and Future Trust Methodology

Autoren: A. S. Albahri Z.T. Al-qaysi Laith H. Alzubaidi et al.

Quelle: Int J Telemed Appl
International Journal of Telemedicine and Applications, Vol 2023 (2023)

Schlagwörter: Artificial neural network, Parallel computing, Artificial intelligence, Interface (matter), Cognitive Neuroscience, Memristive Devices for Neuromorphic Computing, Convolutional neural network, Review Article, Operations research, Cellular and Molecular Neuroscience, Engineering, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Deep Learning for EEG, Electrical and Electronic Engineering, Brain-inspired Computing, Biology, Bubble, Boltzmann machine, Life Sciences, Deep learning, Electroencephalography, Neural Interface Technology, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, Multiple-criteria decision analysis, Process (computing), Brain–computer interface, Operating system, Brain-Computer Interfaces, Physical Sciences, Medicine, Maximum bubble pressure method, Neuroscience

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/37168809
https://doaj.org/article/c067b27d95044a77bb57284bc54673ff

Fully distributed event‐triggered consensus control for linear multiagent systems under DoS attacks

Autoren: Shengli Du Hong Sheng Haoyuan Sun

Quelle: IET Control Theory & Applications, Vol 17, Iss 11, Pp 1485-1494 (2023)

Schlagwörter: 0209 industrial biotechnology, Artificial intelligence, Denial-of-service attack, Consensus, Collective Behavior, Computer Networks and Communications, Memristive Devices for Neuromorphic Computing, Geometry, Control (management), Evolutionary biology, 02 engineering and technology, Network Synchronization in Complex Systems, Quantum mechanics, Multi-Agent Systems, multiagent systems, Engineering, distributed control, Distributed Multi-Agent Coordination and Control, Distributed Optimization, 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Control theory (sociology), FOS: Mathematics, Event-Triggered Control, Electrical and Electronic Engineering, networked control systems, Event (particle physics), Biology, Lyapunov function, Control engineering systems. Automatic machinery (General), Physics, Adaptive control, Computer science, Distributed computing, World Wide Web, Multi-agent system, Function (biology), TJ212-225, Computer Science, Physical Sciences, Zeno's paradoxes, Nonlinear system, discrete event systems, Mathematics, The Internet

Zugangs-URL: https://doaj.org/article/2484bdefe88b4ecaa5d187d9ae1b280c

Volatile and Nonvolatile Dual‐Mode Switching Operations in an Ag‐Ag2S Core‐Shell Nanoparticle Atomic Switch Network

Autoren: Oradee Srikimkaew Saverio Ricci M. Porzani et al.

Quelle: Advanced Electronic Materials, Vol 10, Iss 10, Pp n/a-n/a (2024)

Schlagwörter: Composite material, QC1-999, Memristive Devices for Neuromorphic Computing, Biomedical Engineering, atomic switch networks, Core (optical fiber), Electric apparatus and materials. Electric circuits. Electric networks, FOS: Medical engineering, volatile, Resistive Switching, Cellular and Molecular Neuroscience, Engineering, Nanoparticle, FOS: Electrical engineering, electronic engineering, information engineering, Nanotechnology, electrode spacing, Electrical and Electronic Engineering, Optoelectronics, TK452-454.4, FOS: Nanotechnology, resistive switching, Electronic engineering, Physics, Dual (grammatical number), Life Sciences, Neural Interface Technology, Body Area Nanonetworks, Wireless Nanosensor Networks, Materials science, nonvolatile, Non-volatile memory, silver–silver sulfide nanoparticles, Literature, Physical Sciences, Dual mode, Nanonetworks and Molecular Communication, Non-Volatile Memory, Nanonetworks, Art, Neuroscience

Zugangs-URL: https://doaj.org/article/22a8a6316af744d8ae1e2aebb80e7e7f

XNOR-Bitcount Operation Exploiting Computing-In-Memory With STT-MRAMs

Autoren: Ariana Musello Esteban Garzón Marco Lanuzza et al.

Quelle: IEEE Transactions on Circuits and Systems II: Express Briefs. 70:1259-1263

Schlagwörter: Ferroelectric Devices for Low-Power Nanoscale Applications, Memristive Devices for Neuromorphic Computing, Hyperdimensional Computing, 02 engineering and technology, XNOR gate, Magnetization, Quantum mechanics, 01 natural sciences, 7. Clean energy, spin-transfer torque, Engineering, 0103 physical sciences, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Brain-inspired Computing, Embedded system, Magnetic Skyrmions and Spintronics, Neuromorphic Computing, MAC, bit-quad, Physics, NAND gate, Statistics, STT-MRAM, XNOR-bitcount, Computer hardware, Logic gate, Memory Applications, Spin-transfer torque, Computer science, Atomic and Molecular Physics, and Optics, Energy consumption, Algorithm, Magnetic field, Physics and Astronomy, Electrical engineering, Computing-in-memory, Physical Sciences, DMTJ, Non-Volatile Memory, Energy (signal processing), BNN, CNN, Mathematics