Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.
PLoS One. 2021 Jan 15;16(1):e0245095. doi: 10.1371/journal.pone.0245095. eCollection 2021.
In this study, optical technology is considered as SA issues' solution with the potential ability to increase the speed, overcome memory-limitation, reduce power consumption, and increase output accuracy. So we examine the effect of bio-data encoding and the creation of input images on the pattern-recognition error-rate at the output of optical Vander-lugt correlator. Moreover, we present a genetic algorithm-based coding approach, named as GAC, to minimize output noises of cross-correlating data. As a case study, we adopt the proposed coding approach within a correlation-based optical architecture for counting k-mers in a DNA string. As verified by the simulations on Salmonella whole-genome, we can improve sensitivity and speed more than 86% and 81%, respectively, compared to BLAST by using coding set generated by GAC method fed to the proposed optical correlator system. Moreover, we present a comprehensive report on the impact of 1D and 2D cross-correlation approaches, as-well-as various coding parameters on the output noise, which motivate the system designers to customize the coding sets within the optical setup.
在这项研究中，光学技术被认为是解决 SA 问题的一种方法，具有提高速度、克服存储限制、降低功耗和提高输出精度的潜力。因此，我们研究了生物数据编码和输入图像创建对光学 Vander-lugt 相关器输出模式识别错误率的影响。此外，我们提出了一种基于遗传算法的编码方法，称为 GAC，以最小化互相关数据的输出噪声。作为案例研究，我们在基于相关的光学架构中采用了所提出的编码方法，用于计算 DNA 字符串中的 k-mer。通过对沙门氏菌全基因组的模拟验证，与 BLAST 相比，使用 GAC 方法生成的编码集馈送到所提出的光学相关器系统中，可以将灵敏度和速度分别提高 86%和 81%以上。此外，我们还全面报告了 1D 和 2D 互相关方法以及各种编码参数对输出噪声的影响，这为系统设计人员在光学设置中定制编码集提供了依据。
