[The coding correction of slit diffraction in Hadamard transform spectrometer].

Guang Pu Xue Yu Guang Pu Fen Xi

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

Published: August 2013

According to the principles of Hadamard transform spectrometer and the slit diffraction characteristics, the influence of spectrometer entrance slit diffraction of Hadamard transform spectrometer on the measurement result was analyzed, for the diffraction case, the Hadamard transform spectrometer instrument structure matrix was studied, and the Hadamard transform spectrometer encoding/decoding method was established. The analysis of incident spectral verified the correctness of the coding/ decoding. This method is very important for the high precision measurement of Hadamard transform spectrometer.

Download full-text PDF

Source

Publication Analysis

Top Keywords

hadamard transform
24
transform spectrometer
20
slit diffraction
12
diffraction hadamard
8
hadamard
6
transform
6
spectrometer
6
[the coding
4
coding correction
4
correction slit
4

Similar Publications

The autofluorescence of erythrocyte porphyrins has emerged as a potential method for multi-cancer early detection (MCED). With this method's dependence on research-grade spectrofluorometers, significant improvements in instrumentation are necessary to translate its potential into clinical practice, as with any promising medical technology. To fill this gap, in this paper, we present an automated ratio porphyrin analyzer for cancer screening (ARPA-CS), a low-cost, portable, and automated instrument for MCED via the ratio fluorometry of porphyrins.

View Article and Find Full Text PDF

Charge detection mass spectrometry (CD-MS) is a powerful technique for the analysis of large, heterogeneous biomolecules. By directly measuring the charge states of individual ions, CD-MS can measure the masses from spectra where conventional deconvolution approaches fail due to the lack of isotopic resolution or distinguishable charge states. However, CD-MS is inherently slow because hundreds or thousands of spectra need to be collected to produce adequate ion statistics.

View Article and Find Full Text PDF
Article Synopsis
  • The article introduces a new digital watermarking method that utilizes the Ethereum blockchain, Smart Contracts, and IPFS, coupled with an improved Fast Walsh Hadamard Transform (FWHT) for watermark integration and retrieval.
  • This innovative approach aims to overcome the shortcomings of traditional watermarking methods by removing reliance on third-party platforms, enhancing security through blockchain's decentralized nature.
  • Results indicate that the proposed scheme surpasses existing watermarking techniques in terms of imperceptibility and durability against attacks, positioning it as a viable solution for protecting image copyrights, authentication, and trading.
View Article and Find Full Text PDF

Global discovery lipidomics can provide comprehensive chemical information toward understanding the intricacies of metabolic lipid disorders such as dyslipidemia; however, the isomeric complexity of lipid species remains an analytical challenge. Orthogonal separation strategies, such as ion mobility (IM), can be inserted into liquid chromatography-mass spectrometry (LC-MS) untargeted lipidomic workflows for additional isomer separation and high-confidence annotation, and the emergence of high-resolution ion mobility (HRIM) strategies provides marked improvements to the resolving power ( > 200) that can differentiate small structural differences characteristic of isomers. One such HRIM strategy, high-resolution demultiplexing (HRdm), utilizes multiplexed drift tube ion mobility spectrometry (DTIMS) with post-acquisition algorithmic deconvolution to access high IM resolutions while retaining the measurement precision inherent to the drift tube technique; however, HRdm has yet to be utilized in untargeted studies.

View Article and Find Full Text PDF

Vision Transformer have achieved impressive performance in image super-resolution. However, they suffer from low inference speed mainly because of the quadratic complexity of multi-head self-attention (MHSA), which is the key to learning long-range dependencies. On the contrary, most CNN-based methods neglect the important effect of global contextual information, resulting in inaccurate and blurring details.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!