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Nanochannel-Based Transport in an Interfacial Memristor Can Emulate the Analog Weight Modulation of Synapses

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DenRAM: neuromorphic dendritic architecture with RRAM for efficient temporal processing with delays

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A Highly Reliable RRAM Physically Unclonable Function Utilizing Post-Process Randomness Source

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Multi-State Memristors and Their Applications: An Overview

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Impacts of State Instability and Retention Failure of Filamentary Analog RRAM on the Performance of Deep Neural Network

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Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

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Improvement of State Stability in Multi-Level Resistive Random-Access Memory (RRAM) Array for Neuromorphic Computing

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Investigation of Read Disturb and Bipolar Read Scheme on Multilevel RRAM-Based Deep Learning Inference Engine

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Endurance and Retention Degradation of Intermediate Levels in Filamentary Analog RRAM

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Demonstration of Generative Adversarial Network by Intrinsic Random Noises of Analog RRAM Devices

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Charge-Trap Transistors for CMOS-Only Analog Memory

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The Impact of Thermal Enhance Layers on the Relaxation Effect in Analog RRAM

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Optimization of Multi-Level Operation in RRAM Arrays for In-Memory Computing

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Early-Stage Fluctuation in Low-Power Analog Resistive Memory: Impacts on Neural Network and Mitigation Approach

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A Hybrid CMOS-Memristor Spiking Neural Network Supporting Multiple Learning Rules

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Polarization Pruning: Reliability Enhancement of Hafnia‐Based Ferroelectric Devices for Memory and Neuromorphic Computing

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A ReRAM Macro Using Dynamic Trip-Point-Mismatch Sampling Current-Mode Sense Amplifier and Low-DC Voltage-Mode Write-Termination Scheme Against Resistance and Write-Delay Variation

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Analytic Model for Statistical State Instability and Retention Behaviors of Filamentary Analog RRAM Array and Its Applications in Design of Neural Network

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RRAM Crossbar-Based In-Memory Computation of Anisotropic Filters for Image Preprocessingloa

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Exploring Phase‐Change Memory: From Material Systems to Device Physics

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Impact and Quantization of Short-Term Relaxation effect in Analog RRAM

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Compact Reliability Model of Analog RRAM for Computation-in-Memory Device-to-System Codesign and Benchmark

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Technology Roadmap of Bioinspired Computing Hardware

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A Unified Memory and Hardware Security Module Based on the Adjustable Switching Window of Resistive Memory

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ASAP: An Efficient and Reliable Programming Algorithm for Multi-level RRAM Cell

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Mixed-Signal Neuromorphic Computing Circuits Using Hybrid CMOS-RRAM Integration

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Crossbar-Level Retention Characterization in Analog RRAM Array-Based Computation-in-Memory System

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A New Insight and Modeling of Pulse-to-Pulse Variability in Analog Resistive Memory for On-Chip Training

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Freely switching between ferroelectric and resistive switching in Hf_0.5Zr_0.5O_2 films and its application on high accuracy on-chip deep neural networks

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Edge AI without Compromise: Efficient, Versatile and Accurate Neurocomputing in Resistive Random-Access MemoryPreprint

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A Compact Model for Relaxation Effect in Analog RRAM for Computation-in-Memory System Design and Benchmark

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On the Reliability of Computing-in-Memory Accelerators for Deep Neural Networks

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Improving the Robustness of Neural Networks to Noisy Multi-Level Non-Volatile Memory-based Synapses

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Emerging Non-Volatile Memories for Computation-in-Memory

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Superior Data Retention of Programmable Linear RAM (PLRAM) for Compute-in-Memory Application

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A Process-Variation Robust RRAM-Compatible CMOS Neuron for Neuromorphic System-on-a-Chip

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MoTe2-based synaptic-bridge memristor for brain-inspired computing: neuromorphic performance evaluation using MLP-CNN frameworks

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Intra-array Non-Idealities Modeling and Algorithm Optimization for RRAM-based Computing-in-Memory Applications

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A Mixed-Signal Convolutional Neural Network Using Hybrid CMOS-RRAM Circuits

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Impact of Reset Pulse Width on Gradual Conductance Programming in Al2O3/TiOx-Based RRAM

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Technology-Aware Drift Resilience Analysis of RRAM Crossbar Array Configurations

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TFSRAM: A 249.8TOPS/W Timing-to-First-Spike Compute-in-Memory Neuromorphic Processing Engine With Twin-Column SRAM Synapses

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Reliability of Memristive Devices for High-Performance Neuromorphic Computing: (Invited Paper)

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From Emerging Memory to Novel Devices for Neuromorphic Systems: Consequences for the Reliability Requirements of Memristive Devices

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Energy-Efficient Brain Floating Point Convolutional Neural Network Using Memristors

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Thermal Induced Retention Degradation of RRAM-based Neuromorphic Computing Chips

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High-Efficient Memristor-Based Bayesian Convolutional Neural Networks for Out-of-Distribution Detection by Uncertainty Estimation

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Long-Term Accuracy Enhancement of Binary Neural Networks Based on Optimized Three-Dimensional Memristor Array

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Statistical temperature coefficient distribution in analog RRAM array: impact on neuromorphic system and mitigation method

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Improved Resistive and Synaptic Characteristics in Neuromorphic Systems Achieved Using the Double-Forming Process

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Reliability of Computing-In-Memories: Threats, Detection Methods, and Mitigation Approaches

Chen, Y., & Tsai, Y.-J. (2023) · Proceedings · doi:10.1109/dft59622.2023.10313545 · Cited by 2 · see citing works

A Hybrid Optical-Electrical Analog Deep Learning Accelerator Using Incoherent Optical Signals

Yang, M., Jokar, M. R., Qiu, J., Lou, Q., Liu, Y., Udupa, A., Chong, F. T., Dallesasse, J. M., Feng, M., Goddard, L. L., et al. (2021) · ACM Great Lakes Symposium on VLSI (GLSVLSI) · doi:10.1145/3453688.3461531 · Cited by 2 · see citing works

A Physics of Failure, Kinetic Simulation Model for Reliability of RRAM

Huang, L., & Mosleh, A. (2023) · Annual Reliability and Maintainability Symposium (RAMS) · doi:10.1109/rams51473.2023.10088177 · Cited by 2 · see citing works

Hardware–Software Co-design of Deep Neural Architectures: From FPGAs and ASICs to Computing-in-Memories

Yan, Z., Lu, Q. H., Jiang, W., Yang, L., Hu, X. S., Hu, J., & Shi, Y. (2023) · Springer eBooks · doi:10.1007/978-3-031-39932-9_11 · Cited by 2 · see citing works

Retention Characteristic Optimization Based on Combined Forming Scheme for Resistive Random Access Memory Chip

Zuo, Q., Zheng, X., Zhao, Y., Li, W., Liu, Y., Wu, Q., Lu, Y., Zhao, Y., Zhang, W., Xu, X., et al. (2025) · IEEE Electron Device Letters · doi:10.1109/led.2025.3565496 · Cited by 1 · see citing works

Selective Update for Hardware‐Friendly On‐Chip Training in Distributed Analog In‐Memory Computing Systems

Kang, J., Hong, S., Kim, S., & Kim, S. (2025) · Advanced Intelligent Systems · doi:10.1002/aisy.202500150 · Cited by 1 · see citing works

Physics-Driven In-House Memristor Crossbar Array Model for Image Classification

Canle, D. V., Mohammadidoghozloo, M., Costa, J. D., Leborán, V., Pardo, F., Pereira-Rial, O., Rivadulla, F., Sánchez, V. M. B., & López, P. (2026) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas66217.2026.11562579 · Cited by 1 · see citing works

Design of Resistive Synaptic Devices and Array Architectures for Neuromorphic Computing

Chen, P.-Y. (2018) · Cited by 1 · see citing works

RRAM Device Characterizations and Modelling

Huang, P. C., Gao, B., & Kang, J. (2021) · Springer eBooks · doi:10.1007/978-981-15-6912-8_11

Improving model robustness to weight noise via consistency regularization

Hou, Y., Zhang, Q., Wang, N., & Wu, H. (2024) · Machine Learning Science and Technology · doi:10.1088/2632-2153/ad734a

State-Aware Multibit Write Algorithm for TiOx-Based Resistive Switching Memory Devices

Shi, Y., Sachdev, M., & Miao, G.-X. (2025) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2024.3521653

Noise-Tolerant CIM-DNNs Explained

Meng, F.-H., Lee, E. Y., Wu, Y., Wang, Z., & Lu, W. D. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3621473

Analog In-Memory Computing from a Memory-Agnostic Perspective: Theory, Nonidealities, and Hardware-Aware Training

Sakemi, Y., Awano, H., & Morie, T. (2025) · IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences · doi:10.1587/transfun.2025gci0001

In-memory computing based on CMOS-RRAM hybrid architectures

Esmanhotto, E. (2022) · theses.fr (ABES) · doi:10.70675/1cf79608z3789z4025z8efcz817e8621bdd9

Investigation of resistance fluctuations in ReRAM : physical origin, temporal dependence and impact on memory reliability

Reganaz, L. (2024) · doi:10.70675/8a8c196ez95d7z468czabf2z768bdddceef5

Field- and Temperature-Induced Drift in Multi-Level Al-Doped HfO 2 RRAM

Baroni, A., Wen, J., Pérez, E., Reddy, K. D. S., Uhlmann, M., Pechmann, S., Wenger, C., Ielmini, D., & Zambelli, C. (2026) · IEEE Transactions on Device and Materials Reliability · doi:10.1109/tdmr.2026.3700862

Large-Margin Dynamic Memory Refresh for Persistent In-Memory Computing and Learning

Sebt, S., Leugering, J., Gennis, G., & Cauwenberghs, G. (2026) · IEEE Journal on Emerging and Selected Topics in Circuits and Systems · doi:10.1109/jetcas.2026.3704740

Mitigating Conductance Drift via In-Situ Calibration for Reliable RRAM-Based CIM Edge Inference

Kong, Z., Dong, W.-K., He, J., Yang, Z., Lan, J., Liang, Y., Li, J., Li, Y., & Lin, L. (2026) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas66217.2026.11562039

Non-idealities in artificial synapses

Hamid, S. B., Incorvia, J. A. C., & Liu, S. (2026) · Nature Reviews Physics · doi:10.1038/s42254-026-00957-2

Endurance and Retention Degradation of Intermediate Levels in Filamentary Analog RRAM

Zhao, M., Gao, B., Xi, Y., Xu, F., Wu, H., & Qian, H. (2019) · IEEE Journal of the Electron Devices Society · doi:10.1109/jeds.2019.2943017 · Cited by 38 · see citing works

Reliability Perspective on Neuromorphic Computing Based on Analog RRAM

Wu, H., Zhao, M., Liu, Y., Yao, P., Xi, Y., Li, X., Wu, W., Zhang, Q., Tang, J., Gao, B., et al. (2019) · IEEE International Reliability Physics Symposium proceedings · doi:10.1109/irps.2019.8720609 · Cited by 17 · see citing works

Analytic Model for Statistical State Instability and Retention Behaviors of Filamentary Analog RRAM Array and Its Applications in Design of Neural Network

Huang, P., Xiang, Y., Zhao, Y., Liu, C., Gao, B., Wu, H., Qian, H., Liu, X., & Kang, J. (2018) · Technical digest - International Electron Devices Meeting/Technical digest · doi:10.1109/iedm.2018.8614567 · Cited by 18 · see citing works

Identifying relaxation and random telegraph noises in filamentary analog RRAM for neuromorphic computing

Hu, Q., Gao, B., Tang, J., Hao, Z., Yao, P., Lin, Y., Xi, Y., Zhao, M., Chen, J., Qian, H., et al. (2021) · IEEE Electron Devices Technology & Manufacturing Conference (EDTM) · doi:10.1109/edtm50988.2021.9420888 · Cited by 5 · see citing works

Impact and Quantization of Short-Term Relaxation effect in Analog RRAM

Xi, Y., Gao, B., Tang, J., Mu, X., Xu, F., Yao, P., Li, X., Zhang, W., Zhao, M., Qian, H., et al. (2020) · IEEE Electron Devices Technology & Manufacturing Conference (EDTM) · doi:10.1109/edtm47692.2020.9117902 · Cited by 16 · see citing works