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IR Spectrometers

IR Spectrometers

There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...

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Updated: Jun 5, 2025

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

Published on: November 19, 2020

使用衍射神经网络的光智能光谱仪.

Ze Wang¹, Hang Chen², Jianan Li^1,3

¹School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China.

Nanophotonics (Berlin, Germany)

|December 5, 2024

概括

此摘要是机器生成的。

这项研究引入了一种新型的光学智能光谱仪 (OIS),该光谱仪使用衍射神经网络进行快速,高精度的光谱重建. 这种全光学方法绕过了重的设备和复杂的算法,使各种科学领域的新应用成为可能.

关键词:

视觉情报频谱仪的光学情报.光子神经网络是指光子神经网络.频谱重建的重建

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相关实验视频

Last Updated: Jun 5, 2025

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

Published on: November 19, 2020

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Published on: September 5, 2012

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation

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科学领域:

光学和光子学在光学和光子学.
机器学习机器学习
频谱学是一种光谱学.

背景情况:

光谱重建对于分析远程传感,地质学和医学成像学中的样本组成至关重要.
目前的光谱重建技术受到庞大的硬件和复杂的电子算法的阻碍,限制了性能和应用范围.

研究的目的:

为高精度光谱重建引入一种全新的,灵活的全光学光智能光谱仪 (OIS).
通过低能耗和光速处理来克服现有方法的局限性.

主要方法:

开发一种使用衍射神经网络的光智能光谱仪 (OIS).
用空间连贯和不连贯的光源进行模拟实验.
与简化电气校准模块的集成.
在现实世界的数据集上进行测试,用于光谱重建.

主要成果:

在没有复杂的电子算法的情况下,OIS实现了连贯和不连贯光源的高精度光谱重建.
该系统展示了低能耗和光速处理能力.
与校准模块的集成进一步提高了OIS性能.
在现实数据集上成功进行光谱重建证实了系统的稳定性.

结论:

新型光学智能光谱仪 (OIS) 为光谱重建提供了高精度,高效和灵活的解决方案.
衍射神经网络显示了光谱相互作用和感知应用的巨大潜力.
这项工作推动了光子计算和机器学习在光谱学中的整合.