scholarly journals Comments on “Determination of Background, Signal‐to‐Noise, and Dynamic Range of a Flow Cytometer: A Novel Practical Method for Instrument Characterization and Standardization”

2019 ◽  
Vol 97 (4) ◽  
pp. 423-428
Author(s):  
James C. S. Wood
Keyword(s):  
Dynamic Range ◽  
Practical Method ◽  
Flow Cytometer ◽  
Signal To Noise ◽  
Background Signal

scholarly journals Determination of background, signal-to-noise, and dynamic range of a flow cytometer: A novel practical method for instrument characterization and standardization

2017 ◽  
Vol 91 (11) ◽  
pp. 1104-1114 ◽  
Author(s):  
Claudia Giesecke ◽  
Kristen Feher ◽  
Konrad von Volkmann ◽  
Jenny Kirsch ◽  
Andreas Radbruch ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Practical Method ◽  
Flow Cytometer ◽  
Signal To Noise ◽  
Background Signal

Determination of the Best Emulsion for the Microscopy of Crystals

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.

An Over 120dB Dynamic Range Linear Response Single Exposure CMOS Image Sensor with Two-stage Lateral Overflow Integration Trench Capacitors

2020 ◽  
Vol 2020 (7) ◽  
pp. 143-1-143-6 ◽  
Author(s):  
Yasuyuki Fujihara ◽  
Maasa Murata ◽  
Shota Nakayama ◽  
Rihito Kuroda ◽  
Shigetoshi Sugawa
Keyword(s):  
Linear Response ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Signal To Noise ◽  
Single Exposure ◽  
Two Stage ◽  
Noise Ratio ◽  
Maximum Signal

This paper presents a prototype linear response single exposure CMOS image sensor with two-stage lateral overflow integration trench capacitors (LOFITreCs) exhibiting over 120dB dynamic range with 11.4Me- full well capacity (FWC) and maximum signal-to-noise ratio (SNR) of 70dB. The measured SNR at all switching points were over 35dB thanks to the proposed two-stage LOFITreCs.

scholarly journals A Study of OWA Operators Learned in Convolutional Neural Networks

2021 ◽  
Vol 11 (16) ◽  
pp. 7195
Author(s):  
Iris Dominguez-Catena ◽  
Daniel Paternain ◽  
Mikel Galar
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Practical Method ◽  
Local Information ◽  
Weighted Averaging ◽  
Global Information ◽  
Owa Operator ◽  
Owa Operators ◽  
Ordered Weighted Averaging

Ordered Weighted Averaging (OWA) operators have been integrated in Convolutional Neural Networks (CNNs) for image classification through the OWA layer. This layer lets the CNN integrate global information about the image in the early stages, where most CNN architectures only allow for the exploitation of local information. As a side effect of this integration, the OWA layer becomes a practical method for the determination of OWA operator weights, which is usually a difficult task that complicates the integration of these operators in other fields. In this paper, we explore the weights learned for the OWA operators inside the OWA layer, characterizing them through their basic properties of orness and dispersion. We also compare them to some families of OWA operators, namely the Binomial OWA operator, the Stancu OWA operator and the exponential RIM OWA operator, finding examples that are currently impossible to generalize through these parameterizations.

Quantitative photopyroelectric out-of-phase spectroscopy of amorphous silicon thin films deposited on crystalline silicon

1991 ◽  
Vol 69 (3-4) ◽  
pp. 317-323 ◽  
Author(s):  
Constantinos Christofides ◽  
Andreas Mandelis ◽  
Albert Engel ◽  
Michel Bisson ◽  
Gord Harling
Keyword(s):  
Thin Films ◽  
Optical Absorption ◽  
Absorption Coefficient ◽  
Dynamic Range ◽  
Crystalline Silicon ◽  
Optical Absorption Coefficient ◽  
Si Substrates ◽  
Silicon Thin Films ◽  
Background Compensation

A photopyroelectric spectrometer with real-time and(or) self-normalization capability was used for both conventional transmission and thermal-wave spectroscopic measurements of amorphous Si thin films, deposited on crystalline Si substrates. Optical-absorption-coefficient spectra were obtained from these measurements and the superior dynamic range of the out-of-phase (quadrature) photopyroelectric signal was established as the preferred measurement method, owing to its zero-background compensation capability. An extension of a photopyroelectric theoretical model was established and successfully tested in the determination of the optical absorption coefficient and the thermal diffusivity of the sample under investigation. Instrumental sensitivity limits of βt ≈ 5 × 10−3 were demonstrated.

The Maxwell bridge as a circuit element in electromagnetic feedback seismographs

1968 ◽  
Vol 58 (5) ◽  
pp. 1621-1630
Author(s):  
R. D. Russell ◽  
R. D. Meldrum ◽  
O. G. Jensen
Keyword(s):  
Mechanical Properties ◽  
Effective Mass ◽  
Negative Feedback ◽  
Dynamic Range ◽  
Continuous Operation ◽  
Signal To Noise ◽  
Circuit Element ◽  
Mass Spring ◽  
Principal Advantage ◽  
Impedance Bridge

Abstract The characteristics of a seismograph can be modified by the use of filters or by the application of negative feedback. Both methods provide the same basic signal to noise capabilities, and each has its particular advantages. The principal advantage of the feedback instrument is its flexibility and the possibility of linearity over a greater dynamic range. The application of electrical feedback to a seismometer requires the creation of normally nonexistent electrical input terminals. By incorporating the seismometer into a balanced Maxwell impedance bridge, input terminals can be simulated and the feedback introduced through the bridge. With the use of such negative feedback, it is possible to control individually the effective mass, spring and damping constants of a seismometer. One instrument can thereby simulate seismometers of very different mechanical properties. For example, it is possible to increase the effective mass of a Willmore Mark I seismometer to well over one ton. A feedback seismograph has been constructed using these principles and has been in continuous operation for nearly two years.

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