A Hardware Implementation of Anti-noise Bayesian Deconvolution Algorithm Based on FPGA and Network Port Transmission

In the field of computer science and engineering, hardware acceleration and encryption are key technologies for improving computing power and ensuring information security. FPGAs can be used to accelerate core algorithms and implement information encryption. This experiment focuses on the noise-resistant Bayesian deconvolution algorithm, improving its noise resistance on FPGAs, and achieving hardware acceleration and optimization. It also solves the problem of large data volume by using Ethernet instead of serial ports, significantly improving the efficiency of information processing and system security. It has important engineering significance.

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Published
2024-12-27
DOI
https://doi.org/10.1109/eiecc64539.2024.10929603
Primary Topic
Blind Source Separation Techniques
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article
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article

A Hardware Implementation of Anti-noise Bayesian Deconvolution Algorithm Based on FPGA and Network Port Transmission

Shiwei Feng, Yaning Wang, Boyang Zhang, Yinqi Zhou
Blind Source Separation Techniques
article

A Hardware Implementation of Anti-noise Bayesian Deconvolution Algorithm Based on FPGA and Network Port Transmission

Shiwei Feng, Yaning Wang, Boyang Zhang, Yinqi Zhou
article en

Abstract

In the field of computer science and engineering, hardware acceleration and encryption are key technologies for improving computing power and ensuring information security. FPGAs can be used to accelerate core algorithms and implement information encryption. This experiment focuses on the noise-resistant Bayesian deconvolution algorithm, improving its noise resistance on FPGAs, and achieving hardware acceleration and optimization. It also solves the problem of large data volume by using Ethernet instead of serial ports, significantly improving the efficiency of information processing and system security. It has important engineering significance.

Beijing University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 68%
Blind Source Separation Techniques
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A Hardware Implementation of Anti-noise Bayesian Deconvolution Algorithm Based on FPGA and Network Port Transmission — Shiwei Feng, Yaning Wang, et al. · (2024) | TGRS Research Map | TGRS