The Effect of Pseudorandom Sequence Systematicity on Signal-to-Noise Ratio in Hadamard Transform Ion Mobility Spectrometry

In Hadamard transform ion mobility spectrometry (HT IMS), the signal-to-noise ratio is always lower for non-modified pseudorandom sequences than for modified sequences. Since the use of non-modified modulating pseudorandom sequences is strategically preferable from a duty cycle standpoint, we investigated the change in the interference signal when transitioning from non-modified modulating sequences to sequences modified by the addition of 1,3,5 and 7 zeros. The interfering signal in HT IMS with modified pseudorandom sequences was shown to be mainly random noise for all the cases except for modifying by incorporation of 1 zero. For standard samples of tetraalkylammonium halides, modulation by non-modified pseudorandom sequences is beneficial in the case of small numbers of averaged spectra (below ∼40 averaged spectra compared to any modified pseudorandom sequences except for 1 zero modified and below ∼200 averaged spectra compared to signal averaging ion mobility spectrometry) and worsens the signal-to-noise ratio in the case of large numbers of averaged spectra. Contrarily, modulation by modified pseudorandom sequences is beneficial for any number of averaged spectra, except for very small ones (below 15 averaged spectra compared to modulation by non-modified sequences). Pseudorandom sequence modified with 1 zero incorporation is beneficial in the case of below ∼400 averaged spectra compared to any modified and non-modified pseudorandom sequences. The signal-to-noise ratio in conventional signal averaging mode ion mobility spectrometry is affected by random noise, whereas the HT IMS with non-modified pseudorandom sequences was demonstrated to be primarily affected by a systematic noise-like artefact signal. Because noise-like artefact signals were found to be reproducible, predicting models for interference signals could be generated to improve signal-to-noise ratio. This is significant because non-modified modulating sequences are limited by their poor signal-to-noise ratio. This improvement would increase the viability of non-modified modulating sequences which are preferred because of their higher sample utilization efficiency.

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Ion multiplexing: Maximizing throughput and signal to noise ratio for ion mobility spectrometry

TrAC Trends in Analytical Chemistry ◽

10.1016/j.trac.2019.03.014 ◽

2019 ◽

Vol 116 ◽

pp. 340-345 ◽

Cited By ~ 5

Author(s):

Tobias Reinecke ◽

Cameron N. Naylor ◽

Brian H. Clowers

Keyword(s):

Ion Mobility Spectrometry ◽

Ion Mobility ◽

Signal To Noise Ratio ◽

Signal To Noise ◽

Noise Ratio

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Analytical model for the signal-to-noise-ratio of drift tube ion mobility spectrometers

tm - Technisches Messen ◽

10.1515/teme-2021-0013 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Ansgar T. Kirk ◽

Alexander Bohnhorst ◽

Stefan Zimmermann

Keyword(s):

Ion Mobility ◽

Drift Tube ◽

Signal To Noise Ratio ◽

Resolving Power ◽

Operating Point ◽

Optimum Operating ◽

Signal To Noise ◽

Experimental Parameters ◽

Noise Ratio ◽

Optimum Operating Point

Abstract While the resolving power of drift tube ion mobility spectrometers has been studied and modelled in detail over the past decades, no comparable model exists for the signal-to-noise-ratio. In this work, we develop an analytical model for the signal-to-noise-ratio of a drift tube ion mobility spectrometer based on the same experimental parameters used for modelling the resolving power. The resulting holistic model agrees well with experimental results and allows simultaneously optimizing both resolving power and signal-to-noise-ratio. Especially, it reveals several unexpected relationships between experimental parameters. First, even though reduced initial ion packet widths result in fewer injected ions and reduced amplifier widths result in more noise, the resulting shift of the optimum operating point when reducing both simultaneously leads to a constant signal-to-noise-ratio. Second, there is no dependence of the signal-to-noise-ratio at the optimum operating point on the drift length, as again the resulting shift of the optimum operating point causes all effects to compensate each other.

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Signal-to-noise ratio enhancement of a Hadamard transform spectrometer using a two-dimensional slit-array

Applied Optics ◽

10.1364/ao.56.007188 ◽

2017 ◽

Vol 56 (25) ◽

pp. 7188 ◽

Cited By ~ 3

Author(s):

Mingbo Chi ◽

Yihui Wu ◽

Fang Qian ◽

Peng Hao ◽

Wenchao Zhou ◽

...

Keyword(s):

Signal To Noise Ratio ◽

Hadamard Transform ◽

Two Dimensional ◽

Signal To Noise ◽

Noise Ratio

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The Effect of a Single Defective Mask Element on the Multiplex Advantage in Hadamard Transform Spectroscopy

Applied Spectroscopy ◽

10.1366/0003702894203372 ◽

1989 ◽

Vol 43 (2) ◽

pp. 278-283 ◽

Cited By ~ 8

Author(s):

Stephen A. Dyer ◽

Jin Bae Park

Keyword(s):

Output Signal ◽

Signal To Noise Ratio ◽

Hadamard Transform ◽

Signal To Noise ◽

Noise Ratio ◽

Defective Element ◽

Output Snr

The effect of a single defective mask element on the output signal-to-noise ratio (SNR) for a stationary-mask Hadamard transform (HT) spectrometer is investigated. The decrease in output-SNR from that of an HT spectrometer having a perfect mask is found to be dependent on the amount of energy impinging on the defective element. A method of compensating for the defective mask element is presented. The method is computationally inexpensive and can be fully automated.

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High Sensitivity Snapshot Spectrometer Based on Deep Network Unmixing

Sensors ◽

10.3390/s20247038 ◽

2020 ◽

Vol 20 (24) ◽

pp. 7038

Author(s):

Hui Xie ◽

Zhuang Zhao ◽

Jing Han ◽

Lianfa Bai ◽

Yi Zhang

Keyword(s):

Neural Network ◽

Light Intensity ◽

Signal To Noise Ratio ◽

High Sensitivity ◽

Hadamard Transform ◽

High Signal ◽

Signal To Noise ◽

Compact Structure ◽

Reconstructed Signal ◽

Noise Ratio

Spectral detection provides rich spectral–temporal information with wide applications. In our previous work, we proposed a dual-path sub-Hadamard-s snapshot Hadamard transform spectrometer (Sub-s HTS). In order to reduce the complexity of the system and improve its performance, we present a convolution neural network-based method to recover the light intensity distribution from the overlapped dispersive spectra, rather than adding an extra light path to capture it directly. In this paper, we construct a network-based single-path snapshot Hadamard transform spectrometer (net-based HTS). First, we designed a light intensity recovery neural network (LIRNet) with an unmixing module (UM) and an enhanced module (EM) to recover the light intensity from the dispersive image. Then, we used the reconstructed light intensity as the original light intensity to recover high signal-to-noise ratio spectra successfully. Compared with Sub-s HTS, the net-based HTS has a more compact structure and high sensitivity. A large number of simulations and experimental results have demonstrated that the proposed net-based HTS can obtain a better-reconstructed signal-to-noise ratio spectrum than the Sub-s HTS because of its higher light throughput.

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Determination of the Best Emulsion for the Microscopy of Crystals

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100096886 ◽

1981 ◽

Vol 39 ◽

pp. 32-33

Author(s):

David A. Grano ◽

Kenneth H. Downing

Keyword(s):

Spatial Frequency ◽

Information Transfer ◽

Signal To Noise Ratio ◽

Experimental Situation ◽

Photographic Emulsion ◽

Modulation Transfer ◽

Signal To Noise ◽

Frequency Space ◽

Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

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Experiments in Bright-Field Imaging with Hollow-Cone Illumination

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100097703 ◽

1981 ◽

Vol 39 ◽

pp. 226-227

Author(s):

W. Kunath ◽

K. Weiss ◽

E. Zeitler

Keyword(s):

Signal To Noise Ratio ◽

Carbon Support ◽

Electronic System ◽

Optic Axis ◽

Hollow Cone ◽

Signal To Noise ◽

Bright Field ◽

Noise Ratio ◽

Single Field ◽

Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

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Information capacity and bandwidth limitations in the SEM

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100152392 ◽

1989 ◽

Vol 47 ◽

pp. 84-85

Author(s):

D. C. Joy ◽

R. D. Bunn

Keyword(s):

Signal To Noise Ratio ◽

Critical Dimension ◽

Information Capacity ◽

Acquisition Time ◽

Signal To Noise ◽

Sem Image ◽

Probe Size ◽

Minimum Number ◽

Noise Ratio ◽

Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

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