scholarly journals The Impact of Receiver Aperture Design and Telescope Properties on LIDAR Signal-to-Noise Ratio Improvements

2007 ◽  
Author(s):  
Yasser Hassebo ◽  
Khaled El Sayed
Keyword(s):  
Signal To Noise Ratio ◽  
Lidar Signal ◽  
Signal To Noise ◽  
Noise Ratio ◽  
The Impact

scholarly journals The Geometry of Noise in Color and Spectral Image Sensors

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4487
Author(s):  
Axel Clouet ◽  
Jérôme Vaillant ◽  
David Alleysson
Keyword(s):  
Signal To Noise Ratio ◽  
Spectral Estimation ◽  
Spectral Characteristics ◽  
Color Space ◽  
Color Correction ◽  
Signal To Noise ◽  
Noise Evaluation ◽  
Noise Ratio ◽  
Correction Step ◽  
The Impact

Digital images are always affected by noise and the reduction of its impact is an active field of research. Noise due to random photon fall onto the sensor is unavoidable but could be amplified by the camera image processing such as in the color correction step. Color correction is expressed as the combination of a spectral estimation and a computation of color coordinates in a display color space. Then we use geometry to depict raw, spectral and color signals and noise. Geometry is calibrated on the physics of image acquisition and spectral characteristics of the sensor to study the impact of the sensor space metric on noise amplification. Since spectral channels are non-orthogonal, we introduce the contravariant signal to noise ratio for noise evaluation at spectral reconstruction level. Having definitions of signal to noise ratio for each steps of spectral or color reconstruction, we compare performances of different types of sensors (RGB, RGBW, RGBWir, CMY, RYB, RGBC).

Performance Analysis of Hybrid Fusion in Cognitive Radio Networks

2013 ◽  
Vol 479-480 ◽  
pp. 1027-1031
Author(s):  
Man Man Guo ◽  
Yun Xue Liu ◽  
Wen Qiang Fan
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Signal To Noise Ratio ◽  
Radio Networks ◽  
Base Station ◽  
Good Choice ◽  
Signal To Noise ◽  
Noise Ratio ◽  
The Impact ◽  
Hybrid Fusion

Spectrum sensing is a crucial issue in cognitive radio networks for primary user detection. Cooperative sensing based on energy detection in the cognitive radio network with multiple antennas base-station is considered in this letter. To improve the sensing performance, we investigate hybrid fusion of the observed energies from the base-station and decisions (1bit, hard information) from different cognitive radio (CR) users around the base-station. Further, we present an optimized scheme where the global detection probability can be maximized according to the Neyman-Pearson criterion. Finally the impact of the change of parameters (Signal to Noise Ratio and number of CR users) in the optimized scheme is analyzed. Numerical simulations and extensive analysis confirm that hybrid fusion base on the optimized scheme is a good choice, also, Signal to Noise Ratio (SNR) and number of CR users does not have influence on the optimized scheme

scholarly journals Evaluation of Nonlinear Interference Effects in a Dispersion Managed (DM) Optical Fiber: Performance and Transmission Analysis of 16QAM Modulation using Split Step Fourier Method

2020 ◽  
Author(s):  
Reinhardt Rading
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Optical Fiber ◽  
Signal To Noise Ratio ◽  
Fourier Method ◽  
Interference Effects ◽  
Signal To Noise ◽  
Optical Links ◽  
Noise Ratio ◽  
The Impact

<div>This paper investigates the impact on the optical</div><div>signal-to-noise ratio (OSNR) of the residual per span (RDPS) in a N × 100km dispersion managed system with zero total accumulated dispersion from input to output using split step Fourier method (SSFM) -Monte Carlo simulation. </div><div><br></div><div>This paper shows that the nonlinear interference NLI does in-fact impact the performance yielding different best working power depending on the value of Nx100 km span and the type of dispersion managed link. The paper shows that dispersion uncompensated optical links are preferable to dispersion managed fibers in equalizing NLI effects in long haul optical links.</div>

scholarly journals Signal to Noise Ratio as a Cross-Platform Metric for Intraoperative Fluorescence Imaging

2020 ◽  
Vol 19 ◽  
pp. 153601212091369
Author(s):  
Asmaysinh Gharia ◽  
Efthymios P. Papageorgiou ◽  
Simeon Giverts ◽  
Catherine Park ◽  
Mekhail Anwar
Keyword(s):  
Tumor Cells ◽  
Imaging System ◽  
Signal To Noise Ratio ◽  
Size Variation ◽  
Pixel Size ◽  
Signal To Noise ◽  
Noise Sources ◽  
Noise Measurements ◽  
Noise Ratio ◽  
The Impact

Real-time molecular imaging to guide curative cancer surgeries is critical to ensure removal of all tumor cells; however, visualization of microscopic tumor foci remains challenging. Wide variation in both imager instrumentation and molecular labeling agents demands a common metric conveying the ability of a system to identify tumor cells. Microscopic disease, comprised of a small number of tumor cells, has a signal on par with the background, making the use of signal (or tumor) to background ratio inapplicable in this critical regime. Therefore, a metric that incorporates the ability to subtract out background, evaluating the signal itself relative to the sources of uncertainty, or noise is required. Here we introduce the signal to noise ratio (SNR) to characterize the ultimate sensitivity of an imaging system and optimize factors such as pixel size. Variation in the background (noise) is due to electronic sources, optical sources, and spatial sources (heterogeneity in tumor marker expression, fluorophore binding, and diffusion). Here, we investigate the impact of these noise sources and ways to limit its effect on SNR. We use empirical tumor and noise measurements to procedurally generate tumor images and run a Monte Carlo simulation of microscopic disease imaging to optimize parameters such as pixel size.

Application of Tonal Tracking to Ship Acoustic Signature Feature Identification

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
M. L. Seto
Keyword(s):  
Signal To Noise Ratio ◽  
Background Level ◽  
Feature Identification ◽  
Signal To Noise ◽  
Detection Range ◽  
Detection And Tracking ◽  
Acoustic Signature ◽  
Intensity Changes ◽  
Noise Ratio ◽  
The Impact

A ship’s radiated acoustic signature is known after a range measurement, but it changes from that the longer the ship is in-service. The Ship Signatures Management System (SSMS) provides an organic, real-time capability for a naval ship to monitor its own signature in order to evaluate the impact of proposed actions on its counter-detection range and sensor performance. Ship protection is enhanced through insightful and timely signature data. In particular, this paper discusses the tonal detection and tracking algorithms used to monitor on-board machinery and propeller activity. The paper specifically addresses tonals that appear or disappear as a consequence of changes in the background level, as well as that of crossed tonals. This is of significance because it impacts the SSMS’s ability to attribute cause to changes in the ship acoustic signature. In particular, it is impossible to associate tonals that are time synchronized in their frequency and intensity changes as being created by a single cause (e.g., piece of machinery) with a known tonal set. The use of tonal amplitude and the cause for the signal-to-noise ratio change, in addition to the signal-to-noise ratio, remedies the detection and tracking of tonals that appear/disappear relative to the background. The additional use of tonal width is suggested as a means to remedy the problem of crossed tonals.

scholarly journals Transmission Kikuchi diffraction: The impact of the signal-to-noise ratio

2021 ◽  
pp. 113372
Author(s):  
Tomasz Tokarski ◽  
Gert Nolze ◽  
Aimo Winkelmann ◽  
Łukasz Rychłowski ◽  
Piotr Bała ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio ◽  
The Impact

Speech Recognition in Nonnative versus Native English-Speaking College Students in a Virtual Classroom

2017 ◽  
Vol 28 (05) ◽  
pp. 404-414 ◽  
Author(s):  
Dorothy Neave-DiToro ◽  
Adrienne Rubinstein ◽  
Arlene C. Neuman
Keyword(s):  
College Students ◽  
Speech Recognition ◽  
Signal To Noise Ratio ◽  
Nonnative Speakers ◽  
Mixed Design ◽  
Signal To Noise ◽  
Classroom Acoustics ◽  
English Speaking ◽  
Noise Ratio ◽  
The Impact

Background: Limited attention has been given to the effects of classroom acoustics at the college level. Many studies have reported that nonnative speakers of English are more likely to be affected by poor room acoustics than native speakers. An important question is how classroom acoustics affect speech perception of nonnative college students. Purpose: The combined effect of noise and reverberation on the speech recognition performance of college students who differ in age of English acquisition was evaluated under conditions simulating classrooms with reverberation times (RTs) close to ANSI recommended RTs. Research Design: A mixed design was used in this study. Study Sample: Thirty-six native and nonnative English-speaking college students with normal hearing, ages 18–28 yr, participated. Intervention: Two groups of nine native participants (native monolingual [NM] and native bilingual) and two groups of nine nonnative participants (nonnative early and nonnative late) were evaluated in noise under three reverberant conditions (0.03, 0.06, and 0.08 sec). Data Collection and Analysis: A virtual test paradigm was used, which represented a signal reaching a student at the back of a classroom. Speech recognition in noise was measured using the Bamford–Kowal–Bench Speech-in-Noise (BKB-SIN) test and signal-to-noise ratio required for correct repetition of 50% of the key words in the stimulus sentences (SNR-50) was obtained for each group in each reverberant condition. A mixed-design analysis of variance was used to determine statistical significance as a function of listener group and RT. Results: SNR-50 was significantly higher for nonnative listeners as compared to native listeners, and a more favorable SNR-50 was needed as RT increased. The most dramatic effect on SNR-50 was found in the group with later acquisition of English, whereas the impact of early introduction of a second language was subtler. At the ANSI standard’s maximum recommended RT (0.6 sec), all groups except the NM group exhibited a mild signal-to-noise ratio (SNR) loss. At the 0.8 sec RT, all groups exhibited a mild SNR loss. Conclusion: Acoustics in the classroom are an important consideration for nonnative speakers who are proficient in English and enrolled in college. To address the need for a clearer speech signal by nonnative students (and for all students), universities should follow ANSI recommendations, as well as minimize background noise in occupied classrooms. Behavioral/instructional strategies should be considered to address factors that cannot be compensated for through acoustic design.

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