A Hardware-Friendly Approach Towards Sparse Neural Networks Based on LFSR-Generated Pseudo-Random Sequences-Reference-Cited by-同舟云学术

A Hardware-Friendly Approach Towards Sparse Neural Networks Based on LFSR-Generated Pseudo-Random Sequences

Published:2021-02 Issue:2 Volume:68 Page:751-764
ISSN:1549-8328
Container-title:IEEE Transactions on Circuits and Systems I: Regular Papers
language:
Short-container-title:IEEE Trans. Circuits Syst. I

Author:

Karimzadeh Foroozan^ORCID,Cao Ningyuan^ORCID,Crafton Brian^ORCID,Romberg Justin^ORCID,Raychowdhury Arijit^ORCID

Funder

Semiconductor Research Corporation under Grant Joint University Microelectronics Program (JUMP) Center for Brain-inspired Computing Enabling Autonomous Intelligence

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8919/9325891/09264691.pdf?arnumber=9264691

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3. Design and Analysis of Non-vulnerable PRBS Generation with Internal Shift and XOR of LFSR;Lecture Notes in Electrical Engineering;2024

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5. Towards Energy Efficient DNN accelerator via Sparsified Gradual Knowledge Distillation;2022 IFIP/IEEE 30th International Conference on Very Large Scale Integration (VLSI-SoC);2022-10-03