[go: up one dir, main page]

Shaika et al., 2025 - Google Patents

59 Design and analysis of a quantum FinFET-based memristor with gate diffusion input for neuromorphic computing applications using

Shaika et al., 2025

Document ID
9029398168131042761
Author
Shaika D
Sravanthi M
Karunasree B
Mounikad S
Publication year
Publication venue
Recent Trends in VLSI and Semiconductor Packaging

External Links

Snippet

Neuromorphic computing aims to create computer systems that compete with the architecture and human brain functions. Memristors have been identified as a promising component for implementing synaptic connections in these systems, due to their non-volatile …
Continue reading at books.google.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G06F17/5036—Computer-aided design using simulation for analog modelling, e.g. for circuits, spice programme, direct methods, relaxation methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Cao et al. Emerging dynamic memristors for neuromorphic reservoir computing
Wu et al. Hyperdimensional computing exploiting carbon nanotube FETs, resistive RAM, and their monolithic 3D integration
Li et al. Reproducible ultrathin ferroelectric domain switching for high‐performance neuromorphic computing
Yu Neuro-inspired computing with emerging nonvolatile memorys
Eshraghian et al. Memristive device fundamentals and modeling: Applications to circuits and systems simulation
Chen et al. Ultra-low power Hf 0.5 Zr 0.5 O 2 based ferroelectric tunnel junction synapses for hardware neural network applications
Sharad et al. Ultra low power associative computing with spin neurons and resistive crossbar memory
Shibata et al. Linear and symmetric conductance response of magnetic domain wall type spin-memristor for analog neuromorphic computing
Zhang et al. Spintronic devices for neuromorphic computing
Sengupta et al. Spin-transfer torque magnetic neuron for low power neuromorphic computing
Marrows et al. Neuromorphic computing with spintronics
Li et al. Emerging neuromorphic computing paradigms exploring magnetic skyrmions
Tao et al. Circuit modeling for RRAM-based neuromorphic chip crossbar array with and without write-verify scheme
Angizi et al. Hybrid spin-CMOS polymorphic logic gate with application in in-memory computing
Wang et al. Investigating ferroelectric minor loop dynamics and history effect—Part II: Physical modeling and impact on neural network training
Tran et al. Memcapacitive devices in logic and crossbar applications
Cai et al. Unconventional computing based on magnetic tunnel junction
Mo et al. Beyond-CMOS artificial neuron: A simulation-based exploration of the molecular-FET
Alam et al. Cryogenic in-memory matrix-vector multiplication using ferroelectric superconducting quantum interference device (FE-SQUID)
Pan et al. Beyond-cmos non-boolean logic benchmarking: Insights and future directions
Cha et al. A geometrical optimization rule of the synaptic pass-transistor for a low power analog accelerator
Niu et al. A self-learning magnetic Hopfield neural network with intrinsic gradient descent adaption
Shaika et al. 59 Design and analysis of a quantum FinFET-based memristor with gate diffusion input for neuromorphic computing applications using
Nithya et al. A comprehensive study on the characteristics, complex materials and applications of memristor
Yadav et al. Impact of edge defects on the synaptic characteristic of a ferromagnetic domain-wall device and on on-chip learning