基于FPGA的低秩矩阵恢复算法研究与应用OACSTPCD
Research and Appl ication of Low Rank Matrix Recovery Algorithm Based on FPGA
低秩矩阵恢复算法主要包括鲁棒主成分分析、矩阵补全、低秩表示,由于矩阵补全是一个NP难的问题,低秩表示涉及到字典矩阵,复杂度高,因此本文主要针对鲁棒主成分分析在FPGA上的研究与应用进行了描述,并且在CPU以及FPGA上实现了图像恢复.实验结果表明,基于FPGA的HLS设计相对于传统CPU在速度上得到了数十倍的提高.
The low rank matrix recovery algorithm mainly includes the robust principal component analysis,the matrix completion,the low rank representation.Because the matrix completion is a NP hard problem,the low rank said relates to the dictionary matrix,high complexity.Therefore,this paper mainly described the research and application of the robust principal component analysis in FPGA,and the CPU and FPGA image restoration is realized.The experimental results show …查看全部>>
沈镇;柴志雷
江南大学 物联网工程学院,无锡 214122江南大学 物联网工程学院,无锡 214122
计算机与自动化
低秩矩阵恢复鲁棒主成分分析FPGAHLS
low-rank matrix recoveryrobust principal component analysisFPGAHLS
《单片机与嵌入式系统应用》 2017 (2)
11-14,4
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