从宽带CARS中删除非共振背景,使用基于物理的神经网络
Ryan Muddiman1, Kevin O' Dwyer1, Charles H Camp2
1Department of Electronic Engineering, Maynooth University, Co. Kildare, Ireland.
这项研究引入了一种新的计算系统,使用宽带连贯抗斯托克斯拉曼散射 (BCARS) 光谱学来改进化学分析. 该系统通过计算非共振背景噪声,准确地检索拉曼信号.
科学领域:
- 频谱学是一种光谱学.
- 化学分析 化学分析
- 计算化学的计算化学
背景情况:
- 宽带连贯抗Stokes拉曼散射 (BCARS) 提供快速,高质量的光谱数据.
- 原始BCARS光谱含有非共振电子信号,使化学分析复杂化.
- 以前使用模拟数据的方法对拉曼信号检索显示出了希望.
研究的目的:
- 开发一个改进的计算系统,用于BCARS数据分析.
- 为了准确地从复杂的BCARS光谱中获取纯拉曼信号.
- 为了提高使用BCARS光谱学的化学分析的可靠性.
主要方法:
- 开发了一个集成实验激光特性和模拟易感性的计算系统.
- 采用深度卷积自动编码器网络,对系统特定数据进行训练.
- 使用模拟和实验获得的BCARS数据验证了该方法.
主要成果:
- 新系统成功地绘制了对测量的BCARS反应的敏感性.
- 在模拟和实验数据集上证明了对拉曼信号的准确检索.
- 计算方法有效地减轻了非共振背景干扰.
结论:
- 开发的计算系统提高了从BCARS光谱中提取拉曼信号的准确性.
- 这种方法提高了使用BCARS.进行的化学分析的质量和可靠性.
- 该系统为解决BCARS测量中的光谱干扰提供了强大的解决方案.
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