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Journal articles on the topic 'Signal-to-noise-ratio (SNR)'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Bosworth, B. T., W. R. Bernecky, J. D. Nickila, B. Adal, and G. C. Carter. "Estimating Signal-to-Noise Ratio (SNR)." IEEE Journal of Oceanic Engineering 33, no. 4 (2008): 414–18. http://dx.doi.org/10.1109/joe.2008.2001780.

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Kolar, Petar, Lovro Blažok, and Dario Bojanjac. "NMR spectroscopy threshold signal-to-noise ratio." tm - Technisches Messen 88, no. 9 (2021): 571–80. http://dx.doi.org/10.1515/teme-2021-0008.

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Abstract Ever since noise was spotted and proven to cause problems for the transmission and detection of information through a communication channel, a standard procedure in the process of characterizing a detection system of the communication channel is to determine the level of the lowest detectable signal. In signal processing, this is usually done by determining the so-called threshold signal-to-noise ratio (SNR). This determination is especially important for the communication channels and systems that constantly operate with low-level signals. A good example of such a system is definitel

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Baddour, Natalie, and Zuwen Sun. "Photoacoustics Waveform Design for Optimal Signal to Noise Ratio." Symmetry 14, no. 11 (2022): 2233. http://dx.doi.org/10.3390/sym14112233.

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Time-frequency analysis in waveform engineering can be applied to many detection and imaging systems, such as radar, sonar, and ultrasound to improve their Signal-to-Noise Ratio (SNR). Recently, photoacoustic imaging systems have attracted researchers’ attention. However, the SNR optimization problem for photoacoustic systems has not been fully addressed. In this paper, the one-dimensional SNR optimization of the photoacoustic response to an input waveform with finite duration and energy was considered. This paper applied an eigenfunction optimization approach to find the waveform for optimal

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S., L. M. Hassan, Sulaiman N., S. Shariffudin S., and N. T. Yaakub T. "Signal-to-noise Ratio Study on Pipelined Fast Fourier Transform Processor." Bulletin of Electrical Engineering and Informatics 7, no. 2 (2018): 230–35. https://doi.org/10.11591/eei.v7i2.1167.

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Fast Fourier transform (FFT) processor is a prevailing tool in converting signal in time domain to frequency domain. This paper provides signal-tonoise ratio (SNR) study on 16-point pipelined FFT processor implemented on field-programable gate array (FPGA). This processor can be used in vast digital signal applications such as wireless sensor network, digital video broadcasting and many more. These applications require accuracy in their data communication part, that is why SNR is an important analysis. SNR is a measure of signal strength relative to noise. The measurement is usually in decible

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L. M. Hassan, S., N. Sulaiman, S. S. Shariffudin, and T. N. T. Yaakub. "Signal-to-noise Ratio Study on Pipelined Fast Fourier Transform Processor." Bulletin of Electrical Engineering and Informatics 7, no. 2 (2018): 230–35. http://dx.doi.org/10.11591/eei.v7i2.1167.

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Fast Fourier transform (FFT) processor is a prevailing tool in converting signal in time domain to frequency domain. This paper provides signal-to-noise ratio (SNR) study on 16-point pipelined FFT processor implemented on field-programable gate array (FPGA). This processor can be used in vast digital signal applications such as wireless sensor network, digital video broadcasting and many more. These applications require accuracy in their data communication part, that is why SNR is an important analysis. SNR is a measure of signal strength relative to noise. The measurement is usually in decibl

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Czanner, Gabriela, Sridevi V. Sarma, Demba Ba, et al. "Measuring the signal-to-noise ratio of a neuron." Proceedings of the National Academy of Sciences 112, no. 23 (2015): 7141–46. http://dx.doi.org/10.1073/pnas.1505545112.

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The signal-to-noise ratio (SNR), a commonly used measure of fidelity in physical systems, is defined as the ratio of the squared amplitude or variance of a signal relative to the variance of the noise. This definition is not appropriate for neural systems in which spiking activity is more accurately represented as point processes. We show that the SNR estimates a ratio of expected prediction errors and extend the standard definition to one appropriate for single neurons by representing neural spiking activity using point process generalized linear models (PP-GLM). We estimate the prediction er

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FENG, TIANQUAN. "SIGNAL-TO-NOISE RATIO GAIN VIA CORRELATED NOISE IN AN ENSEMBLE OF NOISY NEURONS." Journal of Biological Systems 28, no. 01 (2020): 111–26. http://dx.doi.org/10.1142/s0218339020500059.

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The collective response of an ensemble of leaky integrate-and-fire neurons induced by local correlated noise is investigated theoretically. Based on the linear response theory, we derive the analytic expression of signal-to-noise ratio (SNR). Numerical results show that the amplitude of internal noise can be increased up to an optimal value where the output SNR reaches a maximum value. Interestingly, we find that the correlated noise between the nearest neurons could lead to the obvious SNR gain. We also show that the SNR can reach unity under condition that the correlated noise between the ne

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Xie, Xiaojuan, Shengliang Peng, and Xi Yang. "Deep Learning-Based Signal-To-Noise Ratio Estimation Using Constellation Diagrams." Mobile Information Systems 2020 (November 6, 2020): 1–9. http://dx.doi.org/10.1155/2020/8840340.

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Signal-to-noise ratio (SNR) estimation is a fundamental task of spectrum management and data transmission. Existing methods for SNR estimation usually suffer from significant estimation errors when SNR is low. This paper proposes a deep learning (DL) based SNR estimation algorithm using constellation diagrams. Since the constellation diagrams exhibit different patterns at different SNRs, the proposed algorithm achieves SNR estimation via constellation diagram recognition, which can be easily handled based on DL. Three DL networks, AlexNet, InceptionV1, and VGG16, are utilized for DL based SNR

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Des Noes, Mathieu. "Distribution of Signal to Noise Ratio and Application to Leakage Detection." IACR Transactions on Cryptographic Hardware and Embedded Systems 2024, no. 2 (2024): 384–402. http://dx.doi.org/10.46586/tches.v2024.i2.384-402.

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In the context of side-channel attacks, the Signal to Noise Ratio (SNR) is a widely used metric for characterizing the information leaked by a device when handling sensitive variables. In this paper, we derive the probability density function (p.d.f.) of the signal to noise ratio (SNR) for the byte value and Hamming Weight (HW) models, when the number of traces per class is large and the target SNR is small. These findings are subsequently employed to establish an SNR threshold, guaranteeing minimal occurrences of false positives. Then, these results are used to derive the theoretical number o

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Khairunnisa, Khairunnisa, Nurkamilia Nurkamilia, and Zuraidah Zuraidah. "Analisis Signal-To-Noise Ratio Pada Sinyal Audio Dengan Teknik Konvolusi." Jurnal ELTIKOM 2, no. 2 (2018): 78–86. http://dx.doi.org/10.31961/eltikom.v2i2.84.

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Di bangku kuliah, derau dan kaitannya dengan kualitas sinyal biasanya dibahas pada mata kuliah pengolahan sinyal. Salah satu metode yang digunakan adalah metode konvolusi. Algoritma yang digunakan cukup kompleks dan tidak mudah cepat dipahami oleh mahasiswa dan ini merupakan tantangan bagi dosen pengajar. Penulis membuat suatu aplikasi yang dapat menampilkan hasil analisis reduksi sinyal audio dengan teknik konvolusi sehingga dapat memberikan pemahaman yang lebih baik kepada mahasiswa sekaligus membuktikan teori yang sudah ada. Langkah-langkah penelitian yang dilakukan adalah menentukan sinyal

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Yen, Benjamin, C. T. Justine Hui, Esther Bergin, et al. "Development of a continuous classroom signal-to-noise ratio measurement system." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 6 (2023): 2284–91. http://dx.doi.org/10.3397/in_2023_0337.

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A successful learning experience requires children to be able to hear what the teacher is saying. To that end, children need a high signal-to-noise ratio (SNR) or speech audibility to hear the teacher under background noise, but SNR in the classrooms may not always be favourable depending on the activities taking place during a school day. We propose a classroom acoustic measurement system to monitor the time-varying SNR under interactive teaching scenarios. Emulating a child listening to the speech made by a teacher, the system utilises two consumer-grade wireless microphones, one attached to

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JIBRIL, Amina, Ashraf Adam AHMAD, and Sagir LAWAN. "Development of Audio Source Separation Algorithm in Noisy Environment Using Compact Kernel Time-Frequency Distribution." Acta Marisiensis. Seria Technologica 21, no. 2 (2024): 6–14. https://doi.org/10.62838/amset-2024-0011.

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This research focuses on the development of a source separation algorithm tailored to significantly enhance audio processing in noisy environments. By utilising advanced signal processing techniques and algorithms based on time-frequency analysis, the study explores the effectiveness of the Compact Kernel Distribution (CKD) for this purpose. Performance was evaluated using key metrics such as Signal-to-Interference Ratio (SIR), Source-to- Distortion Ratio (SDR), and Signal-to-Noise Ratio (SNR). Notable improvements were observed: SIR improved by 4.90% and decreased by 5.36%, while SDR improved

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Choi, Jae-Seung. "Improvement of Signal-to-Noise Ratio for Speech under Noisy Environment." Journal of the Korean Institute of Information and Communication Engineering 17, no. 7 (2013): 1571–76. http://dx.doi.org/10.6109/jkiice.2013.17.7.1571.

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Kamarudin, Mohd Khuzairi Bin Che. "CMOS Based SNR Measurement for Wireless Application." Journal of Applied Engineering & Technology (JAET) 2, no. 1 (2018): 9–13. http://dx.doi.org/10.55447/jaet.02.01.7.

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This paper presents the design of a CMOS based Signal to Noise Ratio (SNR) detection system. The design system is developed using divider, multiplier and an additional multiplier in a feedback loop. The divider in the designed system produce 1/V of the signal and multiplier produces the average squared SNR signal. The last stage in this design circuit is a low pass filter necessary to implement the desired “average” measure of the signal to noise ratio (SNR). From simulation, the output voltage of SNR is 9.167mVp-p and from practical, the output voltage is 13.2mVp-p.

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Anastasia Victor, Agnes Maria Salvi, Gusti Ngurah Sutapa, A. A. Ngurah Gunawan, I. Nengah Sandi, Ni Nyoman Rupiasih, and I. Nengah Simpen. "Optimasi Slice Thickness dengan Nilai Signal to Noise Ratio dan Contrast to Noise Ratio untuk Meningkatkan Kualitas Citra MRI Genu." Kappa Journal 9, no. 1 (2025): 72–77. https://doi.org/10.29408/kpj.v9i1.29591.

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Research has been conducted on the effect of slice thickness variation on the quality of Genu MRI images. This study was conducted at the Radiology Installation of Bali Mandara Hospital using primary data from Genu MRI examination results.The independent variable in this study is the variation of slice thickness values of 3, 5, and 7 mm. There were 30 patientsmeasured and the tissues analyzed were ligament, bone, fat, and noise as background using the ROI method and the segmentation results wereresults were taken at the mean value and standard deviation in the background. The difference in SNR

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Wu, Yuqing. "Optimizing Signal-to-Noise Ratio in MRI Using Fourier-Based Algorithms." Theoretical and Natural Science 109, no. 1 (2025): 99–106. https://doi.org/10.54254/2753-8818/2025.gl23551.

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Signal-to-noise ratio (SNR) is a critical determinant of image quality and diagnostic utility in Magnetic Resonance Imaging (MRI). Fourier-based techniques offer computationally efficient methods to optimize SNR without extending scan duration or requiring any hardware upgrades in some way. This review systematically analyzes and compares six primary Fourier-based SNR optimization methods: (1) frequency-domain filtering, (2) k-space manipulation, (3) spectral subtraction, (4) coil combination, (5) compressed sensing, and (6) transform-domain denoising. Each method is discussed regarding its un

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GINGL, ZOLTAN, PETER MAKRA, and ROBERT VAJTAI. "HIGH SIGNAL-TO-NOISE RATIO GAIN BY STOCHASTIC RESONANCE IN A DOUBLE WELL." Fluctuation and Noise Letters 01, no. 03 (2001): L181—L188. http://dx.doi.org/10.1142/s0219477501000408.

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We demonstrate that signal-to-noise ratio (SNR) can be significantly improved by stochastic resonance in a double well potential. The overdamped dynamical system was studied using mixed signal simulation techniques. The system was driven by wideband Gaussian white noise and a periodic pulse train with variable amplitude and duty cycle. Operating the system in the non-linear response range, we obtained SNR gains much greater than unity. In addition to the classical SNR definition, the ratio of the total power of the signal to the power of the noise part was also measured and it showed better si

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Uaratanawong, Valanon, Chalermchon Satirapod, and Toshiaki Tsujii. "Evaluation of multipath mitigation performance using signal-to-noise ratio (SNR) based signal selection methods." Journal of Applied Geodesy 15, no. 1 (2021): 75–85. http://dx.doi.org/10.1515/jag-2020-0045.

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AbstractSatellite signal strength sometimes decreases when multipath exists. This effect reduces signal quality and can lead to a large static positioning error, even the survey-grade receivers are used. Three signal selection methods based on signal-to-noise ratio (SNR) measurements were proposed. The first was the conventional method, based on elevation-dependent average SNR, the second used a moving average of SNR fluctuation and the third method used NLOS exclusion based on SNR residual clustering by the K-means algorithm. To evaluate the positioning accuracy improvement, the static 1 Hz s

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19

Goldberg, Richard L., and Stephen W. Smith. "Optimization of Signal-to-Noise Ratio for Multilayer Pzt Transducers." Ultrasonic Imaging 17, no. 2 (1995): 95–113. http://dx.doi.org/10.1177/016173469501700202.

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In medical ultrasound imaging, two-dimensional (2-D) array transducers are desirable to implement dynamic focusing and phase aberration correction in two dimensions as well as volumetric imaging. Unfortunately, the small size of a 2-D array element results in a small clamped capacitance and a large electrical impedance near the resonance frequency. This results in poor signal-to-noise ratio (SNR) of the array elements. It has previously been demonstrated that transducers made from multilayer PZT ceramics have lower electrical impedance and greater SNR than comparable single layer elements. A s

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MAKRA, PETER, ZOLTAN GINGL, and LASZLO B. KISH. "SIGNAL-TO-NOISE RATIO GAIN IN NON-DYNAMICAL AND DYNAMICAL BISTABLE STOCHASTIC RESONATORS." Fluctuation and Noise Letters 02, no. 03 (2002): L147—L155. http://dx.doi.org/10.1142/s0219477502000750.

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It has recently been reported that in some systems showing stochastic resonance, the signal-to-noise ratio (SNR) at the output can significantly exceed that at the input; in other words, SNR gain is possible. We took two such systems, the non-dynamical Schmitt trigger and the dynamical double wellpotential, and using numerical and mixed-signal simulation techniques, we examined what SNR gains these systems can provide. In the non-linear response limit, we obtained SNR gains much greater than unity for both systems. In addition to the classical narrow-band SNR definition, we also measured the r

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Gorbunov, Michael, Vladimir Irisov, and Christian Rocken. "The Influence of the Signal-to-Noise Ratio upon Radio Occultation Retrievals." Remote Sensing 14, no. 12 (2022): 2742. http://dx.doi.org/10.3390/rs14122742.

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We study the dependence of radio occultation (RO) inversion statistics on the signal-to-noise ratio (SNR). We use observations from four missions: COSMIC, COSMIC-2, METOP-B, and Spire. All data are processed identically using the same software with the same settings for the retrieval of bending angles, which are compared with reference analyses of the National Oceanic and Atmospheric Administration (NOAA) Global Forecast System. We evaluate the bias, the standard deviation, and the penetration characterized by the fraction of events reaching a specific height. In order to compare SNRs from the

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He, Zhili, and Jizhong Zhou. "Empirical Evaluation of a New Method for Calculating Signal-to-Noise Ratio for Microarray Data Analysis." Applied and Environmental Microbiology 74, no. 10 (2008): 2957–66. http://dx.doi.org/10.1128/aem.02536-07.

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ABSTRACT Signal-to-noise-ratio (SNR) thresholds for microarray data analysis were experimentally determined with an oligonucleotide array that contained perfect-match (PM) and mismatch (MM) probes based upon four genes from Shewanella oneidensis MR-1. A new SNR calculation, called the signal-to-both-standard-deviations ratio (SSDR), was developed and evaluated, along with other two methods, the signal-to-standard-deviation ratio (SSR) and the signal-to-background ratio (SBR). At a low stringency, the thresholds of the SSR, SBR, and SSDR were 2.5, 1.60, and 0.80 with an oligonucleotide and a PC

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Kieser, Robert, Pall Reynisson, and Timothy J. Mulligan. "Definition of signal-to-noise ratio and its critical role in split-beam measurements." ICES Journal of Marine Science 62, no. 1 (2005): 123–30. http://dx.doi.org/10.1016/j.icesjms.2004.09.006.

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Abstract The signal-to-noise ratio (SNR) plays a critical role in any measurement but is particularly important in fisheries acoustics where both signal and noise can change by orders of magnitude and may have large variations. “Textbook situations” exist where the SNR is clearly defined, but fisheries-acoustic measurements are generally not in this category as signal and noise come from a wide range of sources that change with location, depth, and ocean conditions. This paper defines the SNR and outlines its measurement using split-beam data. Its effect on target-strength (TS) measurements is

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Prabawati, Novelsa Chintya, Siti Masrochah, and Sri Mulyati. "Analisis TSE Factor Terhadap Signal to Noise Ratio dan Contrast to Noise Ratio pada Pembobotan T2 Turbo Spin Echo Potongan Axial MRI Brain." Jurnal Imejing Diagnostik (JImeD) 3, no. 2 (2015): 271–76. http://dx.doi.org/10.31983/jimed.v3i2.3198.

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Background: TSE factor is parameters that affect Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR). TSE factor for brain MRI examination is a long TSE factor. There are differences when using TSE factor. At the theory, the brain MRI examination is using TSE factor ≥16 while at Siloam Surabaya Hospital was using TSE factor 14. The writer ever seen some noises at brain MRI image therefore the radiographer doing modification of TSE factor. The purpose of this research are to determine the influence of modification in the TSE factor value against SNR and CNR and to define the SNR and C

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Mladenov, Valeri, Panagiotis Karampelas, Georgi Tsenov, and Vassiliki Vita. "Approximation Formula for Easy Calculation of Signal-to-Noise Ratio of Sigma-Delta Modulators." ISRN Signal Processing 2011 (February 14, 2011): 1–7. http://dx.doi.org/10.5402/2011/731989.

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The signal-to-noise ratio (SNR) is one of the most significant measures of performance of the sigma-delta modulators. An approximate formula for calculation of signal-to-noise ratio of an arbitrary sigma-delta modulator (SDM) has been proposed. Our approach for signal-to-noise ratio computation does not require modulator modeling and simulation. The proposed formula is compared with SNR calculations based on output bitstream obtained by simulations, and the reasons for small discrepancies are explained. The proposed approach is suitable for fast and precise signal-to-noise ratio computation. I

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Thangjai, Warisa, and Sa-Aat Niwitpong. "Confidence Intervals for the Signal-to-Noise Ratio and Difference of Signal-to-Noise Ratios of Log-Normal Distributions." Stats 2, no. 1 (2019): 164–73. http://dx.doi.org/10.3390/stats2010012.

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In this article, we propose approaches for constructing confidence intervals for the single signal-to-noise ratio (SNR) of a log-normal distribution and the difference in the SNRs of two log-normal distributions. The performances of all of the approaches were compared, in terms of the coverage probability and average length, using Monte Carlo simulations for varying values of the SNRs and sample sizes. The simulation studies demonstrate that the generalized confidence interval (GCI) approach performed well, in terms of coverage probability and average length. As a result, the GCI approach is r

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He, Di, Xin Chen, Ling Pei, Lingge Jiang, and Wenxian Yu. "Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic Resonance." Sensors 19, no. 4 (2019): 841. http://dx.doi.org/10.3390/s19040841.

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Noise uncertainty and signal-to-noise ratio (SNR) wall are two very serious problems in spectrum sensing of cognitive radio (CR) networks, which restrict the applications of some conventional spectrum sensing methods especially under low SNR circumstances. In this study, an optimal dynamic stochastic resonance (SR) processing method is introduced to improve the SNR of the receiving signal under certain conditions. By using the proposed method, the SNR wall can be enhanced and the sampling complexity can be reduced, accordingly the noise uncertainty of the received signal can also be decreased.

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Chen, Shutao, Kwan-Long Wong, Jing-Wei Chin, Tsz-Tai Chan, and Richard H. Y. So. "DiffPhys: Enhancing Signal-to-Noise Ratio in Remote Photoplethysmography Signal Using a Diffusion Model Approach." Bioengineering 11, no. 8 (2024): 743. http://dx.doi.org/10.3390/bioengineering11080743.

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Remote photoplethysmography (rPPG) is an emerging non-contact method for monitoring cardiovascular health based on facial videos. The quality of the captured videos largely determines the efficacy of rPPG in this application. Traditional rPPG techniques, while effective for heart rate (HR) estimation, often produce signals with an inadequate signal-to-noise ratio (SNR) for reliable vital sign measurement due to artifacts like head motion and measurement noise. Another pivotal factor is the overlooking of the inherent properties of signals generated by rPPG (rPPG-signals). To address these limi

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Ma, Tian J., and Robert J. Anderson. "Remote Sensing Low Signal-to-Noise-Ratio Target Detection Enhancement." Sensors 23, no. 6 (2023): 3314. http://dx.doi.org/10.3390/s23063314.

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In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Movin

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Siddiqi, Muhammad Hameed, and Yousef Alhwaiti. "Signal-to-Noise Ratio Comparison of Several Filters against Phantom Image." Journal of Healthcare Engineering 2022 (March 26, 2022): 1–11. http://dx.doi.org/10.1155/2022/4724342.

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Image denoising methods are important in order to diminish various kinds of noises, which are presented either capturing the image or distorted during image transmission. Signal-to-noise ratio (SNR) is one of the main barriers which avoids the theoretical observations to be accomplished in practice. In this study, we have utilized various kinds of filtering operators against three various noises, which are the signal-to-noise ratio comparison against the phantom image in spatial and frequency domain. In frequency domain, the average filter is used to smooth the image and frequency domain, and

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Gorbunov, Michael, Vladimir Irisov, and Christian Rocken. "Noise Floor and Signal-to-Noise Ratio of Radio Occultation Observations: A Cross-Mission Statistical Comparison." Remote Sensing 14, no. 3 (2022): 691. http://dx.doi.org/10.3390/rs14030691.

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Multiple radio occultation (RO) missions are currently providing observations that are assimilated by the world’s leading numerical weather prediction centers. These RO missions use the same signals originating from the Global Navigation Satellite Systems (GNSS), but they have different satellite designs and sizes with different antennas and receivers. This results in different noise levels for different missions. Although the amplitude data are characterized by the Signal-to-Noise Ratio (SNR), the noise, to which they are normalized, is not the real Noise Floor (NF) of the RO observations. We

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Kim, Ji-Min, and Seo Il Chang. "Gammatone Feature-based Classification and Signal-to-Noise Ratio Estimation of Aircraft Noise in Combined Noise." Transactions of the Korean Society for Noise and Vibration Engineering 35, no. 3 (2025): 347–54. https://doi.org/10.5050/ksnve.2025.35.3.347.

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Zhu, Shan, Guojun Zhang, Daiyue Wu, et al. "High Signal-to-Noise Ratio MEMS Noise Listener for Ship Noise Detection." Remote Sensing 15, no. 3 (2023): 777. http://dx.doi.org/10.3390/rs15030777.

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Ship noise observation is of great significance to marine environment research and national defense security. Acoustic stealth technology makes a variety of ship noise significantly reduced, which is a new challenge for marine noise monitoring. However, there are few high spatial gain detection methods for low-noise ship monitoring. Therefore, a high Signal-to-Noise Ratio (SNR) MEMS noise listener for ship noise detection is developed in this paper. The listener achieves considerable gain by suppressing isotropic noise in the ocean. The working principle and posterior end signal processing met

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Gebremedhn, W. Wagaye. "Performance Investigation of Channel Noise Effect in Data Transmission Medium Using Signal to Noise Ratio (SNR)." Indonesian Journal of Electrical Engineering and Computer Science 11, no. 2 (2018): 419–23. https://doi.org/10.11591/ijeecs.v11.i2.pp419-423.

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The noise introduced in the channel obviously affects the bit error rate of the communication system and this has direct impact in the security. Here the main problem is that the receiver terminal decoding techniques can lead to wrong interpretation even if the Bit Error Rate (BER) is acceptable. So the main idea here is to introduce high values of Signal to Noise Ratio (SNR) that can improve the bit error rate which exists due to the noise introduced in the wireless channel.

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Chen, Xinwen, Zheng Tan, Jianwei Wang, et al. "Signal-to-Noise Ratio Analysis of Bandpass Sampling Time-Modulated Fourier Transform Spectroscopy." Applied Sciences 14, no. 21 (2024): 10015. http://dx.doi.org/10.3390/app142110015.

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In Bandpass Sampling Fourier Transform Spectroscopy, a comprehensive method for evaluating signal-to-noise ratio (SNR) has not yet been established. This paper employs an energy conservation approach to analyze the relationship of SNR between interferogram and spectra in Bandpass Sampling Time-Modulated Fourier Transform Spectroscopy (BPS-FTS). It systematically presents models for the average SNR of the system interferogram and the average SNR of reconstructed spectra under different parameters. These models are compared with SNR models in traditional Fourier transform spectroscopy (FTS) and

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Kumar, Arun Thitai, Jonathan Ophir, and Thomas A. Krouskop. "Noise Performance and Signal-to-Noise Ratio of Shear Strain Elastograms." Ultrasonic Imaging 27, no. 3 (2005): 145–65. http://dx.doi.org/10.1177/016173460502700302.

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In this paper, we develop a theoretical expression for the signal-to-noise ratio (SNR) of shear strain elastograms. The previously-developed ideas for the axial strain filter (ASF) and lateral strain filter (LSF) are extended to define the concept of the shear strain filter (SSF). Some of our theoretical results are verified using simulations and phantom experiments. The results indicate that the signal-to-noise ratio of shear-strain elastograms ( SNRsse) improves with increasing shear strain and with improvements in system parameters such as the sonographic signal-to-noise ratio ( SNRs) beamw

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Kumru, Yasin, and Hayrettin Köymen. "Signal-to-noise ratio of diverging waves in multiscattering media: Effects of signal duration and divergence angle." Journal of the Acoustical Society of America 151, no. 2 (2022): 955–66. http://dx.doi.org/10.1121/10.0009410.

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In this paper, SNR maximization in coded diverging waves is studied, and experimental verification of the results is presented. Complementary Golay sequences and binary phase shift keying modulation are used to code the transmitted signal. The SNR in speckle and pin targets is maximized with respect to chip signal length. The maximum SNR is obtained in diverging wave transmission when the chip signal is as short a duration as the array permits. We determined the optimum diverging wave profile to confine the transmitted ultrasound energy in the imaging sector. The optimized profile also contrib

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Xu, Pengfei, and Yinjie Jia. "SNR improvement based on piecewise linear interpolation." Journal of Electrical Engineering 72, no. 5 (2021): 348–51. http://dx.doi.org/10.2478/jee-2021-0049.

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Abstract Interpolation improves the resolution of the curve. Based on the stationary characteristics of the signal and the non-stationary characteristics of the noise, the theoretical proof indicates that the piecewise linear interpolation can improve the signal-to-noise ratio, which is further confirmed by simulation results.

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Yang, Kai, Zhitao Huang, Xiang Wang, and Fenghua Wang. "An SNR Estimation Technique Based on Deep Learning." Electronics 8, no. 10 (2019): 1139. http://dx.doi.org/10.3390/electronics8101139.

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Signal-to-noise ratio (SNR) is a priori information necessary for many signal processing algorithms or techniques. However, there are many problems exsisting in conventional SNR estimation techniques, such as limited application range of modulation types, narrow effective estimation range of signal-to-noise ratio, and poor ability to accommodate non-zero timing offsets and frequency offsets. In this paper, an SNR estimation technique based on deep learning (DL) is proposed, which is a non-data-aid (NDA) technique. Second and forth moment (M2M4) estimator is used as a benchmark, and experimenta

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Arifah, Ahda Nur, Yeti Kartikasari, and Emi Murniati. "Analisis Perbandingan Nilai Signal to Noise Ratio (SNR) pada Pemeriksaan MRI Ankle Joint dengan Menggunakan Quad Knee Coil dan Flex/Multipurpose Coil." Jurnal Imejing Diagnostik (JImeD) 3, no. 1 (2017): 220–24. http://dx.doi.org/10.31983/jimed.v3i1.3188.

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Background : Research on the difference comparison the value of Signal To Noise Ratio (SNR) at MRI Ankle Joint examination using Quad Knee Coil and Flex/Multipurpose Coil at the hospital's radiology installation Telogorejo Semarang. Quad knee coil is a volume coil, is a coil that can act as a transmitter and receiver at the same RF signal (transreceiver). Flex / Multipurpose Coil is a surface coil which has a high SNR for a superficial examination (a small organ). The purpose of this research is to know comparison the value of signal to noise ratio (SNR) and higher the value of signal to noise

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Zhang, Beiming, Guoping Chen, and Chun Jiang. "Research on Modulation Recognition Method in Low SNR Based on LSTM." Journal of Physics: Conference Series 2189, no. 1 (2022): 012003. http://dx.doi.org/10.1088/1742-6596/2189/1/012003.

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Abstract Modulation mode recognition of radio signal is a committed step between signal detection and signal demodulation. At present, quite a lot studies have fully proved that deep learning algorithms can effectively identify the modulation pattern of radio signals. However, the sudden decline of recognition accuracy under the condition of low signal-to-noise ratio needs to be continuously studied and solved. Inspired by the excellent performance of recurrent neural network in signal recognition, this article optimizes and improves the existing system methods, realizes the noise reduction pr

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J.S., Ashwin, and Manoharan N. "Audio Denoising Based on Short Time Fourier Transform." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 1 (2018): 89–92. https://doi.org/10.11591/ijeecs.v9.i1.pp89-92.

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This paper presents a novel audio de-noising scheme in a given speech signal. The recovery of original from the communication channel without any noise is a difficult task. Many de-noising techniques have been proposed for the removal of noises from a digital signal. In this paper, an audio denoising technique based on Short Time Fourier Transform (STFT) is implemented. The proposed architecture uses a novel approach to estimate environmental noise from speech adaptively. Here original speech signals are given as input signal. Using AWGN, noises are added to the signal. Then noised signals are

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Takada, Kazumasa, Shin-ichi Satoh, and Akiya Kawakami. "Signal-to-Noise Ratio of Brillouin Grating Measurement with Micrometer-Resolution Optical Low Coherence Reflectometry." Sensors 20, no. 3 (2020): 936. http://dx.doi.org/10.3390/s20030936.

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Signal-dependent speckle-like noise was the dominant noise in a Brillouin grating measurement with micrometer-resolution optical low coherence reflectometry (OLCR). The noise was produced by the interaction of a Stokes signal with beat noise caused by a leaked pump light via square-law detection. The resultant signal-to-noise ratio (SNR) was calculated and found to be proportional to the square root of the dynamic range (DR) defined by the ratio of the Stokes signal magnitude to the variance of the beat noise. The calculation showed that even when we achieved a DR of 20 dB on a logarithmic sca

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Pramana, Kadek Agus Cahya, Ni Putu Rita Jeniyanthi, and I. Bagus Gede Dharmawan. "PENGARUH PENGGUNAAN PARAMETER NUMBER SCAN AVERAGE TERHADAP SIGNAL TO NOISE RATIO DAN SCAN TIME PADA PEMERIKSAAN MAGNETIC RESONANCE IMAGING: STUDI LITERATURE REVIEW." JRI (Jurnal Radiografer Indonesia) 5, no. 1 (2022): 48–53. http://dx.doi.org/10.55451/jri.v5i1.108.

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Background : Signal to Noise Ratio (SNR) is a comparison of the magnitude of the signal amplitude and the magnitude of the amplitude of noise an MRI image that can be used to measure the quality of an MRI image. SNR can be increased by increasing the value of the number scan average (NSA). By increasing the NSA, the SNR will also increase, the scan time will be longer and cause motion artifacts. The purpose of this study was to determine the effect of using the parameter Number Scan Average on the Signal to Noise Ratio and Scan Time on examinations using Magnetic Resonance Imaging modalities.&

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Pramana, Kadek Agus Cahya, Ni Putu Rita Jeniyanthi, and I. Bagus Gede Dharmawan. "PENGARUH PENGGUNAAN PARAMETER NUMBER SCAN AVERAGE TERHADAP SIGNAL TO NOISE RATIO DAN SCAN TIME PADA PEMERIKSAAN MAGNETIC RESONANCE IMAGING: STUDI LITERATURE REVIEW." JRI (Jurnal Radiografer Indonesia) 5, no. 1 (2022): 48–53. http://dx.doi.org/10.55451/jri.v5i1.108.

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Background : Signal to Noise Ratio (SNR) is a comparison of the magnitude of the signal amplitude and the magnitude of the amplitude of noise an MRI image that can be used to measure the quality of an MRI image. SNR can be increased by increasing the value of the number scan average (NSA). By increasing the NSA, the SNR will also increase, the scan time will be longer and cause motion artifacts. The purpose of this study was to determine the effect of using the parameter Number Scan Average on the Signal to Noise Ratio and Scan Time on examinations using Magnetic Resonance Imaging modalities.&

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Zhang, Li, and Xiu Hua Yuan. "Stochastic Resonance in a Single-Mode Laser System with an Input Pulse Signal." Key Engineering Materials 552 (May 2013): 377–83. http://dx.doi.org/10.4028/www.scientific.net/kem.552.377.

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In this paper, we investigated the stochastic resonance (SR) phenomenon in a laser system with correlated pump noise and quantum noise. The signal-to-noise ratio (SNR) is calculated when a square sine pulse signal is added to the system. The effects of the duty cycle of pulse signal and the correlation strength of noises on the SNR are discussed. Some valuable phenomena are investigated to improve the output SNR of laser.

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Kim, Subong, Susan Arzac, Natalie Dokic, et al. "Individual Noise-Tolerance Profiles and Neural Signal-to-Noise Ratio: Insights into Predicting Speech-in-Noise Performance and Noise-Reduction Outcomes." Audiology Research 15, no. 4 (2025): 78. https://doi.org/10.3390/audiolres15040078.

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Background/Objectives: Individuals with similar hearing sensitivity exhibit varying levels of tolerance to background noise, a trait tied to unique individual characteristics that affect their responsiveness to noise reduction (NR) processing in hearing aids. The present study aimed to capture such individual characteristics by employing electrophysiological measures and subjective noise-tolerance profiles, and both were analyzed in relation to speech-in-noise performance and NR outcomes. Methods: From a sample of 42 participants with normal hearing, the neural signal-to-noise ratio (SNR)—a co

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Oo, Thandar, and Pornchai Phukpattaranont. "Signal-to-Noise Ratio Estimation in Electromyography Signals Contaminated with Electrocardiography Signals." Fluctuation and Noise Letters 19, no. 03 (2020): 2050027. http://dx.doi.org/10.1142/s0219477520500273.

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When electromyography (EMG) signals are collected from muscles in the torso, they can be perturbed by the electrocardiography (ECG) signals from heart activity. In this paper, we present a novel signal-to-noise ratio (SNR) estimate for an EMG signal contaminated by an ECG signal. We use six features that are popular in assessing EMG signals, namely skewness, kurtosis, mean average value, waveform length, zero crossing and mean frequency. The features were calculated from the raw EMG signals and the detail coefficients of the discrete stationary wavelet transform. Then, these features are used

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Du, Xiao-Yan, Jian-Ying Li, Wen-Jie Zhao, and Jian-Jun Zhang. "Research on Signal to Noise Ratio Characteristic Influence About Temperature Noise to Infrared Compound Eye Lens Array Imaging." Journal of Nanoelectronics and Optoelectronics 17, no. 3 (2022): 455–64. http://dx.doi.org/10.1166/jno.2022.3232.

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In order to study the effect of temperature noise on the performance of infrared compound eye lens array imaging system, and based on black body infrared radiation and infrared temperature measurement theory, this paper studied the effects of black body radiation temperature and ambient temperature changing on the imaging performance about signal to noise ratio (SNR) and definition of infrared compound eye lens imaging system. Theoretical mathematical model about influence of temperature noise on infrared compound eye imaging system was built. After finishing numerical simulation analysis and

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Klingholz, F. "The measurement of the signal-to-noise ratio (SNR) in continuous speech." Speech Communication 6, no. 1 (1987): 15–26. http://dx.doi.org/10.1016/0167-6393(87)90066-5.

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