Optimal Signal-to-noise Ratio Research Articles

Measuring the primordial gravitational wave background in the presence of other stochastic signals

Standard methodologies for the extraction of the stochastic gravitational wave background (SGWB) from auto- or cross-correlation of interferometric signals often involve the use of a filter function.The standard optimal filter maximizes the signal-to-noise ratio (SNR) between the total SGWB and the noise.We derive expressions for the optimal filter and SNR in the presence of a target SGWB plus other unwanted components. We also generalize the methodology to the case of template-free reconstruction.The formalism allows to easily perform analyses and forecasts that marginalize over foreground signals, such as the typical ΩGW∝ f2/3 background arising from binary coalescence.We demonstrate the methodology with the LISA mission and discuss possible extensions and domains of application.

1/f Noise and Machine Intelligence in a Nonlinear Dopant Atom Network

Noise exists in nearly all physical systems ranging from simple electronic devices such as transistors to complex systems such as neural networks. To understand a system's behavior, it is vital to know the origin of the noise and its characteristics. Recently, it was shown that the nonlinear electronic properties of a disordered dopant atom network in silicon can be exploited for efficiently executing classification tasks through “material learning.” Here, we study the dopant network's intrinsic 1/f noise arising from Coulomb interactions, and its impact on the features that determine its computational abilities, viz., the nonlinearity and the signal‐to‐noise ratio (SNR), is investigated. The findings on optimal SNR and nonlinear transformation of data by this nonlinear network provide a guideline for the scaling of physical learning machines and shed light on neuroscience from a new perspective.

Optimization of multi-receiver SNRs for indoor visible light communication based on modified evolutionary algorithm

Based on indoor visible light communication (VLC) technology, the large-scale LED array can be used for the integration system of communication, positioning and illumination. However, due to the different propagation time between LEDs and receivers, the signal to noise ratio (SNR) is affected by the inter symbol interference (ISI). This paper proposes a multi-receiver SNR optimization method by selecting communicating LEDs in the LED array. The proposed method uses the modified evolutionary algorithm (EA) to obtain the optimal SNR. In the processes of initialization, crossover and mutation operations, instead of general stochastic generation and transformation, the heuristic gene initialization, maximum contributing gene reservation and the minimum contributing gene elimination, which are specially designed for VLC LED selection problem, are proposed to improve the EA. The delay features of different LEDs to receivers are quantitatively analyzed and used as the criteria to gene initialization, crossover and mutation in order to attenuate the ISI. Simulation results reveal that the proposed method converges faster and obtains larger SNRs than the general and the hyper heuristic EA.

Development of rotational pulse-echo ultrasonic propagation imaging system capable of inspecting cylindrical specimens

A rotational pulse-echo ultrasonic propagation imager that can inspect cylindrical specimens for material nondestructive evaluations is proposed herein. In this system, a laser-generated ultrasonic bulk wave is used for inspection, which enables a clear visualization of subsurface defects with a precise reproduction of the damage shape and size. The ultrasonic waves are generated by a Q-switched laser that impinges on the outer surface of the specimen walls. The generated waves travel through the walls and their echo is detected by a Laser Doppler Vibrometer (LDV) at the same point. To obtain the optimal Signal-to-Noise Ratio (SNR) of the measured signal, the LDV requires the sensed surface to be at a right angle to the laser beam and at a predefined constant standoff distance from the laser head. For flat specimens, these constraints can be easily satisfied by performing a raster scan using a dual-axis linear stage. However, this arrangement cannot be used for cylindrical specimens owing to their curved nature. To inspect the cylindrical specimens, a circular scan technology is newly proposed for pulse-echo laser ultrasound. A rotational stage is coupled with a single-axis linear stage to inspect the desired area of the specimen. This system arrangement ensures that the standoff distance and beam incidence angle are maintained while the cylindrical specimen is being inspected. This enables the inspection of a curved specimen while maintaining the optimal SNR. The measurement result is displayed in parallel with the on-going inspection. The inspection data used in scanning are mapped from rotational coordinates to linear coordinates for visualization and post-processing of results. A graphical user interface software is implemented in C++ using a QT framework and controls all the individual blocks of the system and implements the necessary image processing, scan calculations, data acquisition, signal processing and result visualization.

ANALYSIS OF ASIR VARIATION EFFECT TO SNR ON UNENHANCED ABDOMINAL CT SCAN IN UROLITHIASIS

Background: Adaptive Statistical Iterative Reconstruction (ASIR) reconstruction in unenhanced abdominal CT scan reduce the radiation dose from 11.6 mSv to 2.07 mSv. However, the decrease in dose is accompanied by a decrease in image quality. Signal to Noise Ratio (SNR) is one of image quality parameters. Purpose: This study aims to determine the effect of the ASIR method on the optimal Signal to Noise Ratio (SNR) value in unenhanced abdominal CT of urolithiasis in clinical data. Method: 27 samples collected and the SNR was measured on the ASIR reconstruction results at the level of 40%, 50%, 60% by placing the ROI in organ structures with different densities. Result: The results of this study indicate that the ASIR method has a significant effect on the SNR value. Based on the linear regression test, the value was 0.005 ( p< 0.05) and only had an effect of 9.5% on SNR. Conclusion: It can be concluded that the ASIR method affects the optimal SNR value for unenhanced abdominal CT on urolithiasis. The ASIR 60% level was recommended.

Dual-energy CT enterography in evaluation of Crohn's disease: the role of virtual monochromatic images.

To assess the use of virtual monochromatic images (VMI) for discrimination of affected and non-affected bowel walls in patients with Crohn's disease (CD) as well as to compare mural enhancement between patients with and without CD. This retrospective study included 61 patients (47 with CD, 14 without CD). Attenuation value (AV), signal-to noise ratio (SNR), and contrast-to-noise ratio (CNR) were obtained at VMI energy levels from 40 to 110keV in 10keV increment. Analyses were performed among affected and non-affected bowel walls in CD patients, as well as from bowel walls in patients without CD. Image quality and mural enhancement were evaluated at VMI energy levels at 40, 70, and 110keV. At all energy levels of VMI, each quantitative data for AV, SNR, and CNR showed statistically significant difference between diseased and non-diseased bowel walls in CD patients. In the quantitative assessment of patients with and without CD, the optimal AV and SNR were obtained at 40keV, and the optimal CNR was obtained at 70keV. For the qualitative assessment, the best image quality and mural enhancement were obtained at 70keV and 40keV, respectively. VMI are helpful for the differentiation of affected bowel walls in CD patients, providing high diagnostic accuracy.

Pengaruh Variasi Tegangan Tabung Sinar-X terhadap Signal to Noise Ratio (SNR) dengan Penerapan Anode Heel Effect menggunakan Stepwedge

It has been conducted research to determine the effect of X-ray tube voltage variation (kV) on Signal to Noise Ratio (SNR) values by applying the Anode Heel Effect using stepwedge with the addition of 1.5 mm thickness each step. The stepwedge used was 1.5-31.5 mm. The X-ray tube voltage variations used were 40, 50, 60, 70, 80, and 90 kV. Analysis of the effect of X-ray tube voltage variation on SNR values is determined using IMB SPSS Statistics 26 with a simple regression test. The test results showed that variations in X-ray tube voltage affect SNR values, where the greater the variation in X-ray tube voltage then the SNR value would get smaller. The optimal SNR value of 72.685 was obtained at a tube tension of 40 kV and a stepwedge thickness of 27.0 mm.

Increased sensitivity and signal-to-noise ratio in diffusion-weighted MRI using multi-echo acquisitions

Post-mortem diffusion MRI (dMRI) enables acquisitions of structural imaging data with otherwise unreachable resolutions - at the expense of longer scanning times. These data are typically acquired using highly segmented image acquisition strategies, thereby resulting in an incomplete signal decay before the MRI encoding continues. Especially in dMRI, with low signal intensities and lengthy contrast encoding, such temporal inefficiency translates into reduced image quality and longer scanning times. This study introduces Multi Echo (ME) acquisitions to dMRI on a human MRI system - a time-efficient approach, which increases SNR (Signal-to-Noise Ratio) and reduces noise bias for dMRI images. The benefit of the introduced ME-dMRI method was validated using numerical Monte Carlo simulations and showcased on a post-mortem brain of a wild chimpanzee. The proposed Maximum Likelihood Estimation echo combination results in an optimal SNR without detectable signal bias. The combined strategy comes at a small price in scanning time (here 30% additional) and leads to a substantial SNR increase (here white matter: ~ 1.6x, equivalent to 2.6 averages, grey matter: ~ 1.9x, equivalent to 3.6 averages) and a general reduction of the noise bias.

Study on the optimal stochastic resonance of different bistable potential models based on output saturation characteristic and application

Abstract Stochastic resonance (SR) is a kind of physical phenomenon that makes use of noise energy to enhance the signal, but the problem of output saturation generally exists in classcial bistable stochastic resonance (CBSR). To overcome this shortcoming, a few unsaturation models have been established. In view of this, the present study is committed to analyzing and comparing the unsaturation ability of different models more systematically and comprehensively. Firstly, several new piecewise bistable potential models are constructed to supplement the existing unsaturation models and their unsaturation is proved. Then, the higher output signal-to-noise ratio (SNR) of simulated signals shows that the models with linear sides have better unsaturation characteristic and frequency adaptability. Finally, the output SNR and amplitude are chosen as the comprehensive index for evaluating the enhancement performance. Each mod el is applied to process analog and fault signals. The results show that unsaturation capability of piecewise linear bistable stochastic resonance system is best, which is demonstrated again from the optimal output SNR of particle swarm optimization (PSO) algorithm.

Study on the signal-to-noise ratio of Brillouin optical-time domain analyzers.

The signal-to-noise ratio (SNR) of Brillouin optical time-domain analyzers (BOTDA) is modelled and experimentally validated, using direct detection with and without the use of optical pre-amplification. The behavior of SNR as a function of the Brillouin gain and the probe power reaching the photo detection is analyzed in depth using this developed model and checked using two photodetectors with different specifications. It proves that a pre-amplification associated to a good-quality photodetector and a well-matched post-processing filtering can secure the highest SNR for direct-detection BOTDA. Such an optimal SNR presents only a 2.3 dB penalty compared to the ideal shot-noise-limited case that can only be reached using rather sophisticated configurations. In addition, the model here established predicts the SNR at any fiber position in any given experimental condition.

Dynamic Light Scattering: A New Noninvasive Technology for Neonatal Heart Rate Monitoring

Background: Heart rate (HR) detection in premature infants using electrocardiography (ECG) is challenging due to a low signal amplitude and the fragility of the premature skin. Recently, the dynamic light scattering (DLS) technique has been miniaturized, allowing noninvasive HR measurements with a single sensor. Objective: The aim was to determine the accuracy of DLS for HR measurement in infants, compared to ECG-derived HR. Methods: Stable infants with a gestational age of ≥26 weeks, monitored with ECG, were eligible for inclusion. HR was measured with the DLS sensor at 5 different sites for 15 min each. We recorded every 10th second of the DLS-derived HR and the DLS signal-to-noise ratio (SNR), and the ECG-derived HR was extracted for analysis. Patients were randomly divided into 2 groups. In the first group, the optimal SNR cut-off value was determined and then applied to the second group to assess agreement. Results: HR measurements from 31 infants were analyzed. ECG-DLS paired data points were collected at the forehead, an upper extremity, the thorax, a lower extremity, and the abdomen. When applying the international accuracy standard for HR detection, DLS accuracy in the first group (n = 15) was optimal at the forehead (SNR cut-off 1.66). Application of this cut-off to the second group (n = 16) showed good agreement between DLS-derived HR and ECG-derived HR (bias –0.73 bpm; 95% limits of agreement –15.46 and 14.00 bpm) at the forehead with approximately 80% (i.e., 1,066/1,310) of all data pairs remaining. Conclusion: The investigated DLS sensor was sensitive to movement, overall providing less accurate HR measurements than ECG and pulse oximetry. In this study population, specific measurement sites provided excellent signal quality and good agreement with ECG-derived HR.

Head-and-Neck MRI-only radiotherapy treatment planning: From acquisition in treatment position to pseudo-CT generation

PurposeIn context of head-and-neck radiotherapy, this study aims to compare MR image quality according to diagnostic (DIAG) and radiotherapy (RT) setups; and to optimise an MRI-protocol (including 3D T1 and T2-weighted sequences) for dose-planning (based on pseudo-CT generation). Materials and methodsTo compare DIAG and RT setups, signal-to-noise-ratio (SNR) and percentage-image-uniformity (PIU) were computed on T1 images of phantoms and volunteers. Influence of the sample conductivity on SNR was quantified using homemade phantoms. To obtain reliable T1 and T2 images for RT-planning, an experimental design was performed on volunteers by using SNR, contrast-to-noise-ratio (CNR) and mean-opinion-score (MOS). Further, pseudo-CTs were generated from 8 patients T2 images with a state-of-art deep-learning method. These pseudo-CTs were evaluated by mean-absolute-error (MAE) and mean-error (ME). ResultsSNR was higher for DIAG-setup compared to RT-setup (SNR-ratio=1.3). A clear influence of the conductivity on SNR was observed. PIU was higher for DIAG-setup (38.8%) compared to RT-setup (33.5%). Regarding the protocol optimisation, SNR, CNR, and MOS were 20.6, 6.16, and 3.91 for the optimal T1 sequence. For the optimal T2 sequence, SNR, CNR and MOS were 25.6, 44.46 and 4.0. In the whole head-and-neck area, the mean MAE and ME of the pseudo-CTs were 82.8 and -3.9 HU. ConclusionWe quantified the image quality decrease induces by using an RT-setup for head-and-neck radiotherapy. To compensate this decrease, an MRI protocol was optimised by using an experimental design. This protocol of 15minutes provides accurate images which could be used for MRI-dose-planning in clinical practice.

Quantitative assessment of phased array coils with different numbers of receiving channels in terms of signal-to-noise ratio and spatial noise variation in magnetic resonance imaging.

The neuroimaging of humans using 7T magnetic resonance imaging (MRI) has been conducted using phased array (PA) coils with different numbers of receiving channels. PA coils with a high number of channels may offer parallel imaging (PI) with a high reduction (R)-factor, which is enabled via under-sampling and coil geometry (g) factor, increasing the radiofrequency signal sensitivity provided by a small coil. The goals of this study were to assess and validate the coil performance of PA coils with different numbers of receiver (Rx)-channels in and to propose the coil selection guidelines by visualizing 7T brain images. The combined magnetic flux density (||B1||) distributions of four configurations of PA coils—4-, 8-, 12-, and 16-channel Rx-only mode under the local transmit (Tx) mode of birdcage coils—were evaluated using electromagnetic (EM) calculations. These four configurations of PA coils and a local Tx coil were designed and built for a 7T MRI experiment. For 7T brain imaging experiments, all PA coils with (w/) and without (w/o) R-factors were compared in terms of signal-to-noise ratio (SNR) and spatial noise variation (SNV). EM simulation results clearly demonstrated that PA coils with a high number of Rx channels showed more homogeneously distributed ||B1|| fields than a PA coils with a low number of Rx coils. The results of this study demonstrate that a collection of smaller surface coils can contribute to high RF signal sensitivity in terms of the anatomical coverage of the brain and may facilitate PI. With further improvement in coil technology, researchers and clinicians will be provided with PA coils with different numbers of channels, which can ensure the optimum SNR and PI benefits for 7T brain MR imaging.

SNR of MTF calculations in non wide sense stationary systems

Noise in phantom images is propagated to MTF calculated values, increasing their uncertainty. In this work, the phantom that maximizes the signal to noise ratio (SNR) of the MTF is determined as a function of spatial frequency and noise in the images. New analytic expressions for the SNRs of the MTF are derived, and formerly published ones are modified to take into account that real noise is not wide sense stationary (WSS). Five phantoms are used: slit, wire, edge, bar and star-bar. The SNRs are inversely proportional to the frequency in the slit, wire and edge methods. For the phantoms based in periodic pattern, the SNRs are inversely proportional to the squared root of frequency. In the slit and wire methods, an oscillating factor is also present. The loss of the WSS of noise determines the contribution of quantum noise to the SNR. This contribution is negligible in the slit case and remains unaltered in the wire case. The edge, bar and star-bar represent intermediate cases. Finally, ratios of the SNRs between the different methods are provided. These ratios quantify the relative uncertainty of two methods as a function of frequency, noise and the physical dimensions of the phantoms. In this way, these ratios can be used to determine which method produces the optimal SNR in any situation.

Exploring a new method for quantitative sodium MRI in the human upper leg with a surface coil and symmetrically arranged reference phantoms.

The aim of this study is to validate and evaluate the reproducibility of a new setup for the quantification of the tissue sodium concentration (TSC) in the human upper leg muscles with sodium MRI at 3 Tesla. This setup is making use of an emit and receive single loop surface coil together with a set of square, symmetrically arranged reference phantoms. As a second aim, the performances of two MRI protocols for the TSC quantification in the upper leg muscles are compared: one using an ultra-short echo time (UTE) 3-dimensional radial sequence (UTE-protocol), and the other one using standard gradient echo sequence (GRE-protocol). A validation test of the quantification of sodium concentration is performed in phantoms. The bias of the method is estimated and compared between both protocols. The reproducibility of TSC quantification is assessed in phantoms by the coefficient of variation (CV) and compared between both protocols. The reproducibility is also assessed in 11 health volunteers. Signal to noise ratio (SNR) maps are acquired in phantoms with both protocols in order to compare the resulting SNR. The apparatus and post processing were successfully implemented. The bias of the method was smaller than 10% in phantoms (excepted for Na concentration of 10 mmol/L when using the GRE protocol). The reproducibility of the method using symmetrically arranged phantoms was high in phantoms and humans (CV <5%). The GRE-protocol leads to a better SNR than the UTE-protocol in 2D images. The use of symmetrically arranged reference phantoms lead to reproducible results in phantoms and humans. Sodium imaging in the human upper leg with a single loop surface coil should be performed with a standard 2-dimensional GRE protocol if an optimal SNR is needed. However, the quantification of the fast and slow decay time constants of the sodium signal, which plays a role in the TSC quantification, still has to be done with a UTE sequence. Moreover, the quantification of sodium concentration is more accurate with the UTE protocol for small sodium concentrations (<20 mmol).

Fault diagnosis method and application based on unsaturated piecewise linear stochastic resonance.

Signal detection and processing have become an important way to diagnose mechanical faults. The classical bistable stochastic resonance (CBSR) method for signal detection can become saturated, where the amplitude of the output signal gradually stabilizes at a relatively low level instead of increasing with further increases of the input signal amplitude. This leads to difficulty in extracting the weak signals from strong background noise. We studied a new mechanism based on unsaturated piecewise linear stochastic resonance (PLSR). The piecewise linear potential model has a unique structure, which can independently adjust the barrier height and potential wall inclination, so the piecewise linear potential model has a rich potential structure. The rich potential structure makes the potential model unsaturated, thus ensuring that the output signals increase as the input signals increase. In addition, according to the piecewise linear model, the output signal-to-noise ratio (SNR) of the system is deducted. Analysis of the influence of signal strength, potential parameters, and angular frequency on the SNR shows that the optimal SNR can be obtained by adjusting the potential parameters. We propose a weak signal detection method for bearing fault diagnosis. This method can effectively extract the weak fault signals from rolling bearings in a strong noise background. The simulated and experimental bearing fault signals verify that the proposed PLSR method is superior to the CBSR method.

A New Approach to Peak Threshold Estimation for Impulsive Noise Reduction Over Power Line Fading Channels

Impulsive noise (IN) is a major component that degrades signal integrity in power line communication (PLC) systems. PLC systems driven by orthogonal frequency-division multiplexing (OFDM) have Rayleigh distributed amplitudes. Based on the dynamic nature of each OFDM symbol, peak amplitude of the symbol was recently shown to be a suitable threshold for detecting IN, and this technique outperforms the conventional optimal blanking (COB) scheme. In this study, we improve the dynamic peak-based threshold estimation (DPTE) scheme that relies on the OFDM Rayleigh distributed amplitudes by converting the default Rayleigh distribution to uniform distribution to unveil IN with power levels below that of the conventional peak signal. Then, we perform nonlinear mitigation processing on the received signals, whose amplitudes exceed the uniformly distributed amplitude using blanking, a scheme we will refer to as uniformly distributed DPTE (U-DPTE). Our results (based on U-DPTE) significantly outperform the DPTE scheme by up to 4-dB gain in terms of output signal-to-noise ratio (SNR). Additionally and unlike earlier DPTE studies, we propose a novel threshold criterion that compensates the Gaussian noise power-level amplification (after equalization) for achieving the optimal SNR over a log-normal multipath fading channel. The results further reveal the suboptimality of the DPTE scheme over COB.

An Analytical Geometry Optimization Model for Current-Mode Cross-Like Hall Plates.

This paper presents a new analytical geometry optimization model to depict the optimal current sensitivity and signal-to-noise ratio (SNR) for the current-mode Hall devices. The conformal mapping calculation is performed to study the influence of device geometry on the current sensitivity and SNR of the current-mode cross-like Hall plates. The analytical model indicates that a current-mode cross-like Hall plate can achieve optimal current sensitivity and SNR in the device length-to-width ratio (L/W) range of 0.4–0.5 when the thermal noise is taken into account. Three-dimensional (3D) technology computer aided design (TCAD) simulation validates the accuracy of the analytical model. The proposed analytical model provides a geometry design rule to achieve optimal sensitivity and SNR at the same time for the current-mode cross-like Hall plates.

Performance optimization for a phase-sensitive optical time-domain reflectometry based on multiscale matched filtering

Phase-sensitive optical time-domain reflectometry (ϕ-OTDR) has been widely used to interrogate multipoint vibration events in the health monitoring of large-scale infrastructures. Since high signal-to-noise ratio (SNR) is the core parameter for evaluating the performance of ϕ-OTDR, many researchers have presented digital signal processing (DSP) methods for SNR enhancement. However, the DSP methods using fixed parameters cannot achieve the optimum SNR for different vibration events. In addition, although transform domain analysis methods such as wavelet transform could provide multiscale observation for target events, a large amount of computation would be required simultaneously. Matched filtering is a commonly used technique to extract noisy signals in traditional wireless radar systems. Mathematical theory has indicated that matched filtering is also suitable for signal extraction in ϕ-OTDR. The optimization of system performance could be realized when the filter scale matches the length of vibration events. For different lengths of disturbance region, a multiscale matching filtering method has been proposed, which makes it possible to choose appropriate filter scale and finally obtain the optimal SNR. Experimental results have shown that the proposed multiscale matching filtering method could improve the SNR by over 6 dB even under strong noise influence and reach the lowest locating uncertainty of 0.49 m with low time consumption, compared to conventional methods.

The step-edge type HTS rf SQUID coupling with a LC circuit in ultra-low field NMR system

The step-edge type high temperature superconductor (HTS) radio frequency (rf) superconducting quantum interference devices (SQUIDs) were fabricated from YBa2Cu3O7−δ thin films with a field sensitivity of 66 fT/Hz1/2. Even though the sensitivity of the rf SQUID sensor used in the experiments was degraded to 77 fT/Hz1/2 in the magnetic shielded room (MSR), the performance of the rf SQUID sensor was good enough for the ultra-low field (ULF) nuclear magnetic resonance (NMR) experiments at a measurement field of 61.5 μT. With the help of a strictly controlled fast switching circuit and a coupled LC circuit which acted as flux transformer, the signal-to-noise ratio (SNR) of the rf SQUID-based ULF NMR system with different operating points was measured. The optimum SNR was 40 dB which increased significantly by coupling an input coil closely beneath the rf SQUID sensor. The extracted 1/T1 value for pure water sample at 23 ∘C showed the rf SQUID based ULF NMR was an effective system for ULF NMR researches. All above, the direct coupled method and the control circuit show a great potential in the future rf SQUID-based ULF NMR &MRI system.