Code Acceleration Using Memristor-Based Approximate Matrix Multiplier: Application to Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Code Acceleration Using Memristor-Based Approximate Matrix Multiplier: Application to Convolutional Neural Networks

Published:2018-12 Issue:12 Volume:26 Page:2684-2695
ISSN:1063-8210
Container-title:IEEE Transactions on Very Large Scale Integration (VLSI) Systems
language:
Short-container-title:IEEE Trans. VLSI Syst.

Author:

Nourazar Mohsen^ORCID,Rashtchi Vahid^ORCID,Azarpeyvand Ali^ORCID,Merrikh-Bayat Farshad

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Link

http://xplorestaging.ieee.org/ielx7/92/8554317/08374046.pdf?arnumber=8374046

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Hybrid CMOS-Memristor Logic for Boosting the Power-Efficiency in Error Tolerant Applications;2024 37th International Conference on VLSI Design and 2024 23rd International Conference on Embedded Systems (VLSID);2024-01-06

2. Reliable Brain-inspired AI Accelerators using Classical and Emerging Memories;2023 IEEE 41st VLSI Test Symposium (VTS);2023-04-24

3. An Overview of Complex Instability Behaviors Induced by Nonlinearity of Power Electronic Systems with Memristive Load;Energies;2023-03-07

4. An Optimized Deep-Learning-Based Low Power Approximate Multiplier Design;Computer Systems Science and Engineering;2023

5. Design and Analysis of Efficient Exact and In-Exact Reversible 4:2 Compressor Using Qca;2023

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