Electrical Noise Power

1979 ◽  
pp. 200-210
Author(s):  
Rudolf Peter Huebener
Keyword(s):  
Electrical Noise ◽  
Noise Power

Electrical noise power spectrum behavior around threshold in DBR two- or three-section tunable lasers emitting around 1.55 μm

2003 ◽  
Author(s):  
Mikhael Myara ◽  
Philippe Signoret ◽  
Jean-Philippe Tourrenc ◽  
Joel Jacquet ◽  
Bernard P. Orsal ◽  
...  
Keyword(s):  
Power Spectrum ◽  
Tunable Lasers ◽  
Electrical Noise ◽  
Noise Power ◽  
Noise Power Spectrum

Ultimate resolution and information in electron microscopy

1991 ◽  
Vol 49 ◽  
pp. 496-497
Author(s):  
D. Van Dyck
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Transfer Function ◽  
Information Transfer ◽  
Communication Channel ◽  
Structural Information ◽  
Information Rate ◽  
Noise Power ◽  
Signal Power ◽  
Imaging Device

An (electron) microscope can be considered as a communication channel that transfers structural information between an object and an observer. In electron microscopy this information is carried by electrons. According to the theory of Shannon the maximal information rate (or capacity) of a communication channel is given by C = B log2 (1 + S/N) bits/sec., where B is the band width, and S and N the average signal power, respectively noise power at the output. We will now apply to study the information transfer in an electron microscope. For simplicity we will assume the object and the image to be onedimensional (the results can straightforwardly be generalized). An imaging device can be characterized by its transfer function, which describes the magnitude with which a spatial frequency g is transferred through the device, n is the noise. Usually, the resolution of the instrument ᑭ is defined from the cut-off 1/ᑭ beyond which no spadal information is transferred.

Analysis of photographic emulsions for High-Voltage Electron Microscopy

1993 ◽  
Vol 51 ◽  
pp. 452-453 ◽  
Author(s):  
James R. Kremer ◽  
Paul S. Furcinitti ◽  
Eileen O’Toole ◽  
J. Richard McIntosh
Keyword(s):  
Electron Microscope ◽  
Optical Density ◽  
High Voltage ◽  
Noise Power ◽  
Limited Information ◽  
Modulation Transfer ◽  
Transmission Microscopy ◽  
High Voltage Electron Microscopy ◽  
Voltage Range ◽  
Voltage Electron

Characteristics of electron microscope film emulsions, such as the speed, the modulation transfer function, and the exposure dependence of the noise power spectrum, have been studied for electron energies (80-100keV) used in conventional transmission microscopy. However, limited information is available for electron energies in the intermediate to high voltage range, 300-1000keV. Furthermore, emulsion characteristics, such as optical density versus exposure, for new or improved emulsions are usually only quoted by film manufacturers for 80keV electrons. The need for further film emulsion studies at higher voltages becomes apparent when searching for a film to record low dose images of radiation sensitive biological specimens in the frozen hydrated state. Here, we report the optical density, speed and relative resolution of a few of the more popular electron microscope films after exposure to 1MeV electrons.Three electron microscope films, Kodak S0-163, Kodak 4489, and Agfa Scientia 23D56 were tested with a JEOLJEM-1000 electron microscope operating at an accelerating voltage of 1000keV.

Object Detection Using an Ideal Observer Model

2020 ◽  
Vol 2020 (16) ◽  
pp. 41-1-41-7
Author(s):  
Orit Skorka ◽  
Paul J. Kane
Keyword(s):  
Object Detection ◽  
Matched Filter ◽  
Image Sensors ◽  
Ideal Observer ◽  
Noise Power ◽  
Relative Evaluation ◽  
Detection And Identification ◽  
Cross Correlation Analysis ◽  
Observer Model ◽  
The Ideal

Many of the metrics developed for informational imaging are useful in automotive imaging, since many of the tasks – for example, object detection and identification – are similar. This work discusses sensor characterization parameters for the Ideal Observer SNR model, and elaborates on the noise power spectrum. It presents cross-correlation analysis results for matched-filter detection of a tribar pattern in sets of resolution target images that were captured with three image sensors over a range of illumination levels. Lastly, the work compares the crosscorrelation data to predictions made by the Ideal Observer Model and demonstrates good agreement between the two methods on relative evaluation of detection capabilities.

scholarly journals Study on Time Reversal Maximum Ratio Combining in Underwater Acoustic Communications

2021 ◽  
Vol 11 (4) ◽  
pp. 1509
Author(s):  
Anbang Zhao ◽  
Caigao Zeng ◽  
Juan Hui ◽  
Keren Wang ◽  
Kaiyu Tang
Keyword(s):  
Time Reversal ◽  
Signal To Noise Ratio ◽  
Spatial Diversity ◽  
Single Element ◽  
Noise Power ◽  
Theoretical Derivation ◽  
Underwater Acoustic ◽  
Maximum Ratio Combining ◽  
Weight Coefficients ◽  
Output Snr

Time reversal (TR) can achieve temporal and spatial focusing by exploiting spatial diversity in complex underwater environments with significant multipath. This property makes TR useful for underwater acoustic (UWA) communications. Conventional TR is realized by performing equal gain combining (EGC) on the single element TR output signals of each element of the vertical receive array (VRA). However, in the actual environment, the signal-to-noise ratio (SNR) and the received noise power of each element are different, which leads to the reduction of the focusing gain. This paper proposes a time reversal maximum ratio combining (TR-MRC) method to process the received signals of the VRA, so that a higher output SNR can be obtained. The theoretical derivation of the TR-MRC weight coefficients indicates that the weight coefficients are only related to the input noise power of each element, and are not affected by the multipath structure. The correctness of the derivation is demonstrated with the experimental data of the long-range UWA communications conducted in the South China Sea. In addition, the experimental results illustrate that compared to the conventional TR, TR-MRC can provide better performance in terms of output SNR and bit error rate (BER) in UWA communications.

Sign in / Sign up

Export Citation Format

Share Document