Related references
Note: Only part of the references are listed.Full-Circuit Implementation of Transformer Network Based on Memristor
Chao Yang et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS (2022)
Three-Dimensional Neuromorphic Computing System With Two-Layer and Low-Variation Memristive Synapses
Hongyu An et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2022)
ACE-SNN: Algorithm-Hardware Co-design of Energy-Efficient & Low-Latency Deep Spiking Neural Networks for 3D Image Recognition
Gourav Datta et al.
FRONTIERS IN NEUROSCIENCE (2022)
Brain-Like Initial-Boosted Hyperchaos and Application in Biomedical Image Encryption
Hairong Lin et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2022)
NEAT: Nonlinearity Aware Training for Accurate, Energy-Efficient, and Robust Implementation of Neural Networks on 1T-1R Crossbars
Abhiroop Bhattacharjee et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2022)
Memristive Circuit Implementation of Context-Dependent Emotional Learning Network and Its Application in Multitask
Cong Xu et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2022)
Multilayer Memristive Neural Network Circuit Based on Online Learning for License Plate Detection
Renao Yan et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2022)
Regulating memristive neuronal dynamical properties via excitatory or inhibitory magnetic field coupling
Zhenghui Wen et al.
NONLINEAR DYNAMICS (2022)
A Novel Memristive Chaotic Neuron Circuit and Its Application in Chaotic Neural Networks for Associative Memory
Chaoxun Pan et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2021)
Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing
Youngeun Kim et al.
NEURAL NETWORKS (2021)
Memristor-based neural network circuit with weighted sum simultaneous perturbation training and its applications
Cong Xu et al.
NEUROCOMPUTING (2021)
Visual explanations from spiking neural networks using inter-spike intervals
Youngeun Kim et al.
SCIENTIFIC REPORTS (2021)
Revisiting Batch Normalization for Training Low-Latency Deep Spiking Neural Networks From Scratch
Youngeun Kim et al.
FRONTIERS IN NEUROSCIENCE (2021)
Neural Bursting and Synchronization Emulated by Neural Networks and Circuits
Hairong Lin et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS (2021)
Training Energy-Efficient Deep Spiking Neural Networks with Single-Spike Hybrid Input Encoding
Gourav Datta et al.
2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) (2021)
Spiking Neural Networks for Computational Intelligence: An Overview
Shirin Dora et al.
BIG DATA AND COGNITIVE COMPUTING (2021)
A review of learning in biologically plausible spiking neural networks
Aboozar Taherkhani et al.
NEURAL NETWORKS (2020)
Memristors for Neuromorphic Circuits and Artificial Intelligence Applications
Enrique Miranda et al.
MATERIALS (2020)
A Memristor-Based Spiking Neural Network With High Scalability and Learning Efficiency
Zhenyu Zhao et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS (2020)
Supervised learning in spiking neural networks: A review of algorithms and evaluations
Xiangwen Wang et al.
NEURAL NETWORKS (2020)
Spiking neurons with spatiotemporal dynamics and gain modulation for monolithically integrated memristive neural networks
Qingxi Duan et al.
NATURE COMMUNICATIONS (2020)
A Multi-Stable Memristor and its Application in a Neural Network
Hairong Lin et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS (2020)
Going Deeper in Spiking Neural Networks: VGG and Residual Architectures
Abhronil Sengupta et al.
FRONTIERS IN NEUROSCIENCE (2019)
Graphene-ferroelectric transistors as complementary synapses for supervised learning in spiking neural network
Yangyang Chen et al.
NPJ 2D MATERIALS AND APPLICATIONS (2019)
An On-Chip Trainable and the Clock-Less Spiking Neural Network With 1R Memristive Synapses
Aditya Shukla et al.
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS (2018)
Memristive Model for Synaptic Circuits
Yang Zhang et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS (2017)
Efficient Memristor Model Implementation for Simulation and Application
Xiaoping Wang et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2017)
A Compact Memristor-Based Dynamic Synapse for Spiking Neural Networks
Miao Hu et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2017)
RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks
Aayush Ankit et al.
PROCEEDINGS OF THE 2017 54TH ACM/EDAC/IEEE DESIGN AUTOMATION CONFERENCE (DAC) (2017)
Neuronal Synapse as a Memristor: Modeling Pair- and Triplet-Based STDP Rule
Weiran Cai et al.
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS (2015)
VTEAM: A General Model for Voltage-Controlled Memristors
Shahar Kvatinsky et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS (2015)
Supervised Learning Using Spike-Timing-Dependent Plasticity of Memristive Synapses
Yu Nishitani et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)
Components of Working Memory and Visual Selective Attention
Bryan R. Burnham et al.
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN PERCEPTION AND PERFORMANCE (2014)
Bottom-Up and Top-Down Attention: Different Processes and Overlapping Neural Systems
Fumi Katsuki et al.
NEUROSCIENTIST (2014)
TEAM: ThrEshold Adaptive Memristor Model
Shahar Kvatinsky et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS (2013)
Generalized Memristive Device SPICE Model and its Application in Circuit Design
Chris Yakopcic et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2013)
A New Supervised Learning Algorithm for Spiking Neurons
Yan Xu et al.
NEURAL COMPUTATION (2013)
The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web]
Li Deng
IEEE SIGNAL PROCESSING MAGAZINE (2012)
Top-down modulation: bridging selective attention and working memory
Adam Gazzaley et al.
TRENDS IN COGNITIVE SCIENCES (2012)
Supervised Learning in Spiking Neural Networks with ReSuMe: Sequence Learning, Classification, and Spike Shifting
Filip Ponulak et al.
NEURAL COMPUTATION (2010)
The missing memristor found
Dmitri B. Strukov et al.
NATURE (2008)
A new correlation-based measure of spike timing reliability
S Schreiber et al.
NEUROCOMPUTING (2003)
Share Paper
