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Journal articles on the topic 'Signal to noise ratio'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

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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2

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

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<p>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 de-noising 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 s

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3

Yang, Ren Di, and Yan Li Zhang. "Denoising of ECG Signal Based on Empirical Mode Decomposition and Adaptive Noise Cancellation." Applied Mechanics and Materials 40-41 (November 2010): 140–45. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.140.

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To remove the noises in ECG and to overcome the disadvantage of the denoising method only based on empirical mode decomposition (EMD), a combination of EMD and adaptive noise cancellation is introduced in this paper. The noisy ECG signals are firstly decomposed into intrinsic mode functions (IMFs) by EMD. Then the IMFs corresponding to noises are used to reconstruct signal. The reconstructed signal as the reference input of adaptive noise cancellation and the noisy ECG as the basic input, the de-noised ECG signal is obtained after adaptive filtering. The de-noised ECG has high signal-to-noise

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Selvaraj, Poovarasan, and E. Chandra. "Ideal ratio mask estimation using supervised DNN approach for target speech signal enhancement." Journal of Intelligent & Fuzzy Systems 42, no. 3 (2022): 1869–83. http://dx.doi.org/10.3233/jifs-211236.

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The most challenging process in recent Speech Enhancement (SE) systems is to exclude the non-stationary noises and additive white Gaussian noise in real-time applications. Several SE techniques suggested were not successful in real-time scenarios to eliminate noises in the speech signals due to the high utilization of resources. So, a Sliding Window Empirical Mode Decomposition including a Variant of Variational Model Decomposition and Hurst (SWEMD-VVMDH) technique was developed for minimizing the difficulty in real-time applications. But this is the statistical framework that takes a long tim

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C, Shraddha, Chayadevi M L, Anusuya M A, and Vani H Y. "Enhancing Noise Reduction with Bionic Wavelet and Adaptive Filtering." Inteligencia Artificial 27, no. 74 (2024): 214–26. http://dx.doi.org/10.4114/intartif.vol27iss74pp214-226.

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Speech signals often contain different forms of background and environmental noise. For the development of an efficient speech recognition system, it is essential to preprocess noisy speech signals to reduce the impact of these disturbances. Notably, prior research has paid limited attention to pink and babble noises. This gap in knowledge inspired us to develop and implement hybrid algorithms tailored to handle these specific noise types. We introduce a hybrid method that combines the Bionic Wavelet transform with Adaptive Filtering to enhance signal strength. The performance of this method i

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Memduh; TAŞCIOĞLU, KÖSE. "Signal-to-noise ratio estimation of noisy transient signals." Communications Faculty Of Science University of Ankara 57, no. 1 (2015): 11–19. http://dx.doi.org/10.1501/commua1-2_0000000084.

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Najafipour, Abbas, Abbas Babaee, and S. Mohammad Shahrtash. "Comparing the trustworthiness of signal-to-noise ratio and peak signal-to-noise ratio in processing noisy partial discharge signals." IET Science, Measurement & Technology 7, no. 2 (2013): 112–18. http://dx.doi.org/10.1049/iet-smt.2012.0113.

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8

Smith, Robert C., and Robert C. Lange. "Signal to Noise Ratio." Critical Reviews in Diagnostic Imaging 42, no. 2 (2001): 135–40. http://dx.doi.org/10.3109/20014091086711.

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Johnson, Don. "Signal-to-noise ratio." Scholarpedia 1, no. 12 (2006): 2088. http://dx.doi.org/10.4249/scholarpedia.2088.

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10

Kharchenko, O. I., and V. M. Kartashov. "Standing out of Radiosignals on the Background of Noises Based on the Effect of Stochastic Resonance." Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, no. 86 (September 30, 2021): 39–44. https://doi.org/10.20535/radap.2021.86.39-44.

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The main and most difficult problem of signals receiving is the problem of noise immunity to find the best methods of receiving radio signals in the presence of interference. The analysis of radio signals standing out with the help of stochastic resonance effect are given. The linear frequency modulated and phase-code-manipulated signals are considered as an object of research. Linear frequency modulated phase-code-manipulated signals are widely used in radar and telecommunication systems. The phenomenon of stochastic resonance is a type of cooperative effect of noise and weak signal under a c

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11

Gudiškis, Andrius. "HEART BEAT DETECTION IN NOISY ECG SIGNALS USING STATISTICAL ANALYSIS OF THE AUTOMATICALLY DETECTED ANNOTATIONS / ŠIRDIES DŪŽIŲ NUSTATYMAS IŠ IŠKRAIPYTŲ EKG SIGNALŲ ATLIEKANT AUTOMATIŠKAI APTIKTŲ ATSKAITŲ STATISTINĘ ANALIZĘ." Mokslas – Lietuvos ateitis 7, no. 3 (2015): 300–303. http://dx.doi.org/10.3846/mla.2015.787.

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This paper proposes an algorithm to reduce the noise distortion influence in heartbeat annotation detection in electrocardiogram (ECG) signals. Boundary estimation module is based on energy detector. Heartbeat detection is usually performed by QRS detectors that are able to find QRS regions in a ECG signal that are a direct representation of a heartbeat. However, QRS performs as intended only in cases where ECG signals have high signal to noise ratio, when there are more noticeable signal distortion detectors accuracy decreases. Proposed algorithm uses additional data, taken from arterial bloo

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Kropotov, Y. A., A. A. Belov, and A. Y. Prockuryakov. "Increasing signal/acoustic interference ratio in telecommunications audio exchange by adaptive filtering methods." Information Technology and Nanotechnology, no. 2416 (2019): 271–76. http://dx.doi.org/10.18287/1613-0073-2019-2416-271-276.

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The paper deals with the issues of increasing signal/noise ratio in telecommunication audio exchange systems. The study of characteristics of speech signals and acoustic noises, such as mathematical expectation, dispersion, relative intensity of acoustic speech signals and various types of acoustic noises and interference is carried out. It is shown that in the design of telecommunications systems, in particular loudspeaker systems operating under the influence of external acoustic noise of high intensity, it is necessary to solve the problem of developing algorithms to effectively suppress th

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Han, Xiao Gang, Mei Quan Liu, and Qin Lei Sun. "The Design and Implementation of Adaptive Noise Cancellation for Magnetic Flux Leakage Test Signal." Applied Mechanics and Materials 441 (December 2013): 393–96. http://dx.doi.org/10.4028/www.scientific.net/amm.441.393.

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In the application of magnetic flux leakage (MFL) nondestructive testing, the signal will be disturbed by varying noises. It seriously affects the accuracy of detection judgment result. This paper describes the design of least mean square (LMS) noise cancellation for MFL signal and the implementation based on ARM platform. Two giant magnetoresistive sensors are used to measure the signal, one sensor for MFL signal (with noise) and the other one for the noise signal. They are inputted to the noise cancellation to obtain pure MFL signals. Experimental results show that the LMS noise cancellation

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14

Rao*, G. Manmadha, Raidu Babu D.N, Krishna Kanth P.S.L, Vinay B., and Nikhil V. "Reduction of Impulsive Noise from Speech and Audio Signals by using Sd-Rom Algorithm." International Journal of Recent Technology and Engineering 10, no. 1 (2021): 265–68. http://dx.doi.org/10.35940/ijrte.a5943.0510121.

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Removal of noise is the heart for speech and audio signal processing. Impulse noise is one of the most important noise which corrupts different parts in speech and audio signals. To remove this type of noise from speech and audio signals the technique proposed in this work is signal dependent rank order mean (SD-ROM) method in recursive version. This technique is used to replace the impulse noise samples based on the neighbouring samples. It detects the impulse noise samples based on the rank ordered differences with threshold values. This technique doesn’t change the features and tonal qualit

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G.Manmadha, Rao, Raidu Babu D.N, Krishna Kanth P.S.L, B.Vinay, and V.Nikhil. "Reduction of Impulsive Noise from Speech and Audio Signals by using Sd-Rom Algorithm." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 1 (2021): 265–68. https://doi.org/10.35940/ijrte.A5943.0510121.

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Removal of noise is the heart for speech and audio signal processing. Impulse noise is one of the most important noise which corrupts different parts in speech and audio signals. To remove this type of noise from speech and audio signals the technique proposed in this work is signal dependent rank order mean (SD-ROM) method in recursive version. This technique is used to replace the impulse noise samples based on the neighbouring samples. It detects the impulse noise samples based on the rank ordered differences with threshold values. This technique doesn’t change the features and tonal

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16

Zhang, Jian, Ji Zhang, Bo Zha, Jiahui Deng, and Zhiwei Shao. "Study on Noise Reduction Processing of Nondestructive Testing Signals Based on Wavelet Analysis." E3S Web of Conferences 618 (2025): 02017. https://doi.org/10.1051/e3sconf/202561802017.

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During the execution of nondestructive testing (NDT) tasks, various noise signals interfere with the collected data, leading to signal distortion. As a result, directly evaluating the damage of mebers based on noisy signals becomes exceedingly challenging. To mitigate the adverse effects of noise, this study employs wavelet analysis theory to analyze denoising parameters for ultrasonic testing signals contaminated by noise. The findings reveal that when the wavelet basis is set to coif5 and the decomposition level is 2, the denoised signal achieves the highest signal-to-noise ratio (SNR), effe

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Buhaiov, M. V. "Method of Complex Envelope Processing for Signal Edges Detection." Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, no. 92 (June 30, 2023): 54–59. https://doi.org/10.20535/radap.2023.92.54-59.

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Problem statement. The need of information processing automation in modern radio monitoring systems stimulates development of flexible methods for signal detection and its parameters estimation in time domain. A priori uncertainty of signal time-frequency structure complicates the automatic determination of signals edges. Purpose. The purpose of the article is subsequent automation of radio frequency spectrum analysis process by developing and implementing a method for determining signals time edges under conditions of a known noise power and signal-to-noise ratio. Method. To determine signal

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18

CHAPEAU-BLONDEAU, FRANÇOIS, and JULIO ROJAS-VARELA. "NONLINEAR SIGNAL PROPAGATION ENHANCED BY NOISE VIA STOCHASTIC RESONANCE." International Journal of Bifurcation and Chaos 10, no. 08 (2000): 1951–59. http://dx.doi.org/10.1142/s0218127400001249.

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A model is developed for a nonlinear line of coupled noisy threshold elements. The propagation on the line of various information-carrying signals, periodic, aperiodic or random, is analyzed. Different measures quantifying the efficacy of the propagation are calculated, including signal-to-noise ratio, cross-correlation measures, information-theoretic measures and propagation length. These measures are shown to be improvable by the addition of noise. These results establish a new instance of the nonlinear phenomenon of stochastic resonance under the form of a noise-enhanced propagation applyin

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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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20

Jenkin, Robin. "Contrast Signal to Noise Ratio." Electronic Imaging 2021, no. 17 (2021): 186–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.17.avm-186.

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The detection and recognition of objects is essential for the operation of autonomous vehicles and robots. Designing and predicting the performance of camera systems intended to supply information to neural networks and vision algorithms is nontrivial. Optimization has to occur across many parameters, such as focal length, f-number, pixel and sensor size, exposure regime and transmission schemes. As such numerous metrics are being explored to assist with these design choices. Detectability index (SNRI) is derived from signal detection theory as applied to imaging systems and is used to estimat

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Davidson, Steven J. "The Signal-to-Noise Ratio." Emergency Medicine News 26, no. 8 (2004): 38. http://dx.doi.org/10.1097/00132981-200408000-00023.

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22

Lan, Jin Hui, and Zhi Cheng Liu. "A Novel Noise Elimination Method for MEMS Sensor." Key Engineering Materials 483 (June 2011): 779–83. http://dx.doi.org/10.4028/www.scientific.net/kem.483.779.

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It is inevitable that measured signals are contaminated with noise when MEMS sensor is used for an outdoor measurement. So the obtained signals need noise elimination, which is one of key technologies for signal conditioning. In this paper, a novel noise elimination method based on algorithm of blind source separation (BSS) for MEMS sensor is proposed to separate the source signals from the mixed signals with noises. The BSS algorithm based on maximum signal noise ratio (SNR) is a method of global optimal property, using the characteristic that SNR is maximal when statistically independent sou

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Muhammad Basharat, Muhammad Basharat, Ming Ding Ming Ding, Yang Li Yang Li, Hongwei Cai Hongwei Cai, and Jiancheng Fang Jiancheng Fang. "Noise reduction and signal to noise ratio improvement in magneto-optical polarization rotation measurement." Chinese Optics Letters 16, no. 8 (2018): 081201. http://dx.doi.org/10.3788/col201816.081201.

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Chinomso, Maduakolam Francis, Samson Dauda Yusuf, Ibrahim Umar, and Abdullahi Abubakar Mundi. "Analysis of Savitzky-Golay Filter for Electrocardiogram De-Noising Using Daubechies Wavelets." EDUCATUM Journal of Science, Mathematics and Technology 9, no. 2 (2022): 113–28. http://dx.doi.org/10.37134/ejsmt.vol9.2.13.2022.

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Electrocardiogram (ECG) examination is of great importance in medical diagnosis of the cardiac disease, but wrong interpretation due to noise interference in the signal could be dangerous as this may lead to wrong diagnoses of patient’s heart condition. De-noising helps to reduce the noise level for a better interpretation of the signals. In this study, an analysis of Savitzky-Golay (S-G) filter for ECG de-noising using Daubechies wavelets has been carried out using MATLAB version 2015a. Noisy ECG signals downloaded from physionet.org under MIT-BIH arrhythmia database was de-noised using S-G f

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Maduakolam, Francis Chinomso, Samson Dauda Yusuf, and Ibrahim Umar. "Analysis of Savitzky-Golay Filter for Electrocardiogram De-Noising Using Daubechies Wavelets." ASEANA: Science and Education Journal, no. 1 (December 29, 2021): 34–48. https://doi.org/10.53797/aseana.v1i2.3.2021.

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Electrocardiogram (ECG) examination is of great importance in medical diagnosis of the cardiac disease, but wrong interpretation due to noise interference in the signal could be dangerous as this may lead to wrong diagnoses of patient’s heart condition. De-noising helps to reduce the noise level for a better interpretation of the signals. In this study, an analysis of Savitzky-Golay (S-G) filter for ECG de-noising using Daubechies wavelets has been carried out using MATLAB version 2015a. Noisy ECG signals downloaded from physionet.org under MIT-BIH arrhythmia database was de-noised using S-G f

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Zhang, Dengyong, Shanshan Wang, Feng Li, et al. "An ECG Signal De-Noising Approach Based on Wavelet Energy and Sub-Band Smoothing Filter." Applied Sciences 9, no. 22 (2019): 4968. http://dx.doi.org/10.3390/app9224968.

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Electrocardiographic (ECG) signal is essential to diagnose and analyse cardiac disease. However, ECG signals are susceptible to be contaminated with various noises, which affect the application value of ECG signals. In this paper, we propose an ECG signal de-noising method using wavelet energy and a sub-band smoothing filter. Unlike the traditional wavelet threshold de-noising method, which carries out threshold processing for all wavelet coefficients, the wavelet coefficients that require threshold de-noising are selected according to the wavelet energy and other wavelet coefficients remain u

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Roy, Asmita, Enakshi Chakrabarti, and Prabir Banerjee. "Study of Cognitive Radio Performance in Relation to Signal to Noise Ratio and Modulation Scheme." International Journal of Scientific Engineering and Research 6, no. 6 (2018): 75–80. https://doi.org/10.70729/ijser172654.

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Kovtun, S., A. Vetoshkin, and V. Kutsenko. "INTERFERENCE RESISTANCE OF A CORRELATION RECEIVER AT A LIMITED OBSERVATION INTERVAL." Наукові праці Державного науково-дослідного інституту випробувань і сертифікації озброєння та військової техніки 14, no. 4 (2022): 51–58. http://dx.doi.org/10.37701/dndivsovt.14.2022.06.

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The article considers the possibility of increasing the capability of detecting a useful radio signal against the background of noise and simultaneously reducing the possibility of mistaking noise fluctuations for a signal. Moreover, if it is absent then the Neumann-Pearson statistical test should be used. This criterion is a partial case from the class of criteria consisting in the calculation of the likelihood ratio and does not require knowledge of a priori probabilities of the presence or absence a useful signal while constructing an optimal receiver and Bayesian methods are used. Th

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Chernoyarov, Oleg, Alexey Glushkov, Vladimir Litvinenko, Yuliya Litvinenko, and Serguei Pergamenshchikov. "Signal-to-noise ratio measurement for the signals with constant amplitude." Journal of Physics: Conference Series 2388, no. 1 (2022): 012072. http://dx.doi.org/10.1088/1742-6596/2388/1/012072.

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Abstract A digital meter measuring the signal-to-noise ratio in the channel for transmitting discrete information with a constant amplitude of symbols that are the phase or frequency shift keyed signals is proposed. The desired value of the signal-to-noise ratio is determined based on the number of exceedings of the threshold level by the modulus of the logarithm of the ratio of the amplitudes of the received and previous symbols in the sample of a specified size, while the meter itself is invariant to the absolute levels of the signal and noise. It is shown that in the channel with Gaussian n

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Peng, Liang, Shengliang Fang, Youchen Fan, Mengtao Wang, and Zhao Ma. "A Method of Noise Reduction for Radio Communication Signal Based on RaGAN." Sensors 23, no. 1 (2023): 475. http://dx.doi.org/10.3390/s23010475.

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Radio signals are polluted by noise in the process of channel transmission, which will lead to signal distortion. Noise reduction of radio signals is an effective means to eliminate the impact of noise. Using deep learning (DL) to denoise signals can reduce the dependence on artificial domain knowledge, while traditional signal-processing-based denoising methods often require knowledge of the artificial domain. Aiming at the problem of noise reduction of radio communication signals, a radio communication signal denoising method based on the relativistic average generative adversarial networks

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Lin, Tingting, Xiaokang Yao, Sijia Yu, and Yang Zhang. "Electromagnetic Noise Suppression of Magnetic Resonance Sounding Combined with Data Acquisition and Multi-Frame Spectral Subtraction in the Frequency Domain." Electronics 9, no. 8 (2020): 1254. http://dx.doi.org/10.3390/electronics9081254.

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As an advanced groundwater detection method, magnetic resonance sounding (MRS) has received more and more attention. However, the biggest challenge is that MRS measurements always suffer with a bad signal-to-noise ratio (SNR). Aiming at the problem of noise interference in MRS measurement, we propose a novel noise-suppression approach based on the combination of data acquisition and multi-frame spectral subtraction (DA-MFSS). The pure ambient noise from the measurement area is first collected by the receiving coil, and then the noisy MRS signal is recorded following the pulse moments transmitt

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Nimmagadda, Padmaja, Kondru Ayyappa Swamy, Samuda Prathima, Sushma Chintha, and Zachariah Callottu Alex. "Short-term uncleaned signal to noise threshold ratio based endto-end time domain speech enhancement in digital hearing aids." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 1 (2022): 131–38. https://doi.org/10.11591/ijeecs.v27.i1.pp131-138.

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This paper presents the improvements in the combined solution for the noise estimation and the speech enhancement in digital hearing aids in time domain. This study focuses on the single channel statistical temporal speech enhancement using adaptive Wiener filtering. In this technique, the noise is updated based on the short-term uncleaned signal to noise threshold ratio (ST-USNTR) of the frame. It works best if and only if the background noise level is low compared to that of speech of interest. We considered the time domain algorithms in order to consider the time varying nature of speech si

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Fan, Yi Bo, Feng Shou Gu, and Andrew Ball. "Acoustic Emission Monitoring of Mechanical Seals Using MUSIC Algorithm Based on Higher Order Statistics." Key Engineering Materials 413-414 (June 2009): 811–16. http://dx.doi.org/10.4028/www.scientific.net/kem.413-414.811.

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This paper presents the use of the MUSIC algorithm improved by higher order statistics (HOS) to extract key features from the noisy acoustic emission (AE) signals. The low signal-to-noise ratio of AE signals has been identified as a main barrier to the successful condition monitoring of pump mechanical seals. Since HOS methods can effectively eliminate Gaussian noise, it is possible in theory to identify a change in seal conditions from AE measurements even with low signal-to-noise ratios. Tests conducted on a test rig show that the developed algorithm can successfully detect the AE signal gen

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Nimmagadda, Padmaja, Kondru Ayyappa Swamy, Samuda Prathima, Sushma Chintha, and Zachariah Callottu Alex. "Short-term uncleaned signal to noise threshold ratio based end-to-end time domain speech enhancement in digital hearing aids." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 1 (2022): 131. http://dx.doi.org/10.11591/ijeecs.v27.i1.pp131-138.

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This paper presents the improvements in the combined solution for the noise estimation and the speech enhancement in digital hearing aids in time domain. This study focuses on the single channel statistical temporal speech enhancement using adaptive Wiener filtering. In this technique, the noise is updated based on the short-term uncleaned signal to noise threshold ratio (ST-USNTR) of the frame. It works best if and only if the back ground noise level is low compared to that of speech of interest. We considered the time domain algorithms in order to consider the time varying nature of speech s

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Khan, Junaid Bahadar, Tariqullah Jan, Ruhul Amin Khalil, Nasir Saeed, and Muhannad Almutiry. "An Efficient Multistage Approach for Blind Source Separation of Noisy Convolutive Speech Mixture." Applied Sciences 11, no. 13 (2021): 5968. http://dx.doi.org/10.3390/app11135968.

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This paper proposes a novel efficient multistage algorithm to extract source speech signals from a noisy convolutive mixture. The proposed approach comprises two stages named Blind Source Separation (BSS) and de-noising. A hybrid source prior model separates the source signals from the noisy reverberant mixture in the BSS stage. Moreover, we model the low- and high-energy components by generalized multivariate Gaussian and super-Gaussian models, respectively. We use Minimum Mean Square Error (MMSE) to reduce noise in the noisy convolutive mixture signal in the de-noising stage. Furthermore, th

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Degtyaryov, Alexander, and Alexander Kozhemyakin. "Matched Filter Design Method for White Noise and Non-Gaussian Noise Conditions." Infocommunications and Radio Technologies 5, no. 2 (2022): 253–59. http://dx.doi.org/10.29039/2587-9936.2022.05.2.19.

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A method for synthesizing a matched filter for conditions of simultaneous action of white noise and non-Gaussian noise is proposed. The method is based on the representation of the matched filter as a linear system that implements an integral transformation with a real kernel. Noise, non-Gaussian noise and signal are considered to be frequency limited. The signal-to-noise ratio at the reference point in time is determined. The expansion of the correlation function of the interference and the signal into a series of count functions and the resulting signal-to-noise ratio give an equation that a

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Li, Jian Jun, and Jian Feng Zhao. "Detection of Life Characteristic Signals Based on High Order Statistics." Applied Mechanics and Materials 239-240 (December 2012): 807–10. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.807.

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Life parameters signal has characteristics of extremely low frequency, low signal-to-noise ratio, and the easy submerged in strong clutter noises. The method for detecting life signal based on filter bank and high order statistics is presented, in which neither the Gaussian supposition of the observed signal, nor a prior information about the waveform and arrival time of the observed signal is necessary. The principle of method is to separate the spectrum of input signal into many narrow frequency bands, whose Sub-band signal is followed by a short-time estimation of higher-order statistics so

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Çataltaş, Özcan. "Effect of noise reduction on PLSR modeling in near infrared spectroscopy using denoising autoencoder." New Trends in Computer Sciences 3, no. 1 (2025): 38–48. https://doi.org/10.3846/ntcs.2025.24139.

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In this study, a deep learning-based denoising autoencoder approach is proposed to increase the robustness of near-infrared spectroscopy data to random noise and improve quantitative modeling accuracy. Artificial Gaussian noise at four different levels (10, 15, 20, and 25 dB) was added to the near-infrared spectra obtained from milk samples to mimic the real measurement conditions. The noisy spectra were denoised by processing with an autoencoder architecture consisting of fully connected layers. The noise removal performance is quantitatively evaluated with both theoretical and measured signa

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Kremenetskaya, Yana, and Sergey Markov. "Comparative analysis of interference, noise and losses in the mobile communication systems in millimeter wave range." Computational Problems of Electrical Engineering 8, no. 1 (2018): 18–25. http://dx.doi.org/10.23939/jcpee2018.01.018.

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The article analyzes the approaches to the mathematical modeling of mobile systems in the millimeter wave range. The architecture of a mobile network using Radio over Fiber (RoF) technology is considered which is proposed for forming and transmitting the millimeter-wave signals via fiber-optic communication lines. The noise of the optical heterodyne used for the formation of radio signals is analyzed. The mathematical analysis of the components of the energy budget of the radio link in the millimeter wave range is carried out on the basis of a study of the fundamental physical aspects that aff

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Барковська, Олеся Юріївна, and Антон Олегович Гаврашенко. "Research of the impact of noise reduction methods on the quality of audio signal recovery." Інформаційно-керуючі системи на залізничному транспорті 29, no. 3 (2024): 57–65. http://dx.doi.org/10.18664/ikszt.v29i3.313606.

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The subject of the study is the analysis of various filtering algorithms for the quality of the resulting audio files. The importance of audio line filtering has grown significantly in recent years due to its key role in a variety of applications such as speech reduction and artificial intelligence. Taking into account the growing demand for solving problems related to speech recognition, the processing of audio series becomes important for determining the accuracy and efficiency of the obtained solution.The purpose of the work is to study the impact of noise suppression methods on the quality

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Fathima, S. Yasmin, G. V. S. Karthik, M. Zia Ur Rahman, and A. Lay-Ekuakille. "Efficient Artifact Elimination in Cardiac Signals using Variable Step Size Adaptive Noise Cancellers." International Journal of Measurement Technologies and Instrumentation Engineering 2, no. 1 (2012): 35–51. http://dx.doi.org/10.4018/ijmtie.2012010103.

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In this paper several variable step size adaptive filter structures for extracting high resolution electrocardiographic (ECG) signals are presented which estimates the deterministic components of the ECG signal and removes the artifacts. The noise canceller minimizes the mean square error (MSE) between the input noisy ECG signal and noise reference. Different noise canceller structures are proposed to remove diverse forms of artifacts: power line interference, baseline wander, muscle artifacts and electrode motion artifacts. The proposed implementation is suitable real time applications, where

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Hasan, Fadhil Sahib. "Chaotic signals denoising using empirical mode decomposition inspired by multivariate denoising." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1352. http://dx.doi.org/10.11591/ijece.v10i2.pp1352-1358.

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Empirical mode decomposition (EMD) is an effective noise reduction method to enhance the noisy chaotic signal over additive noise. In this paper, the intrinsic mode functions (IMFs) generated by EMD are thresholded using multivariate denoising. Multivariate denoising is multivariable denosing algorithm that is combined wavelet transform and principal component analysis to denoise multivariate signals in adaptive way. The proposed method is compared at a various signal to noise ratios (SNRs) with different techniques and different types of noise. Also, scale dependent Lyapunov exponent (SDLE) i

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Fadhil, Sahib Hasan. "Chaotic signals denoising using empirical mode decomposition inspired by multivariate denoising." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1352–58. https://doi.org/10.11591/ijece.v10i2.pp1352-1358.

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Empirical mode decomposition (EMD) is an effective noise reduction method to enhance the noisy chaotic signal over additive noise. In this paper, the intrinsic mode functions (IMFs) generated by EMD are thresholded using multivariate denoising. Multivariate denoising is multivariable denosing algorithm that is combined wavelet transform and principal component analysis to denoise multivariate signals in adaptive way. The proposed method is compared at a various signal to noise ratios (SNRs) with different techniques and different types of noise. Also, scale dependent Lyapunov exponent (SDLE) i

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Andreiev, O., V. Tsyporenko, V. Tsyporenko, Y. Andreieva, O. Dubyna, and I. Puleko. "ELECTROMAGNETIC COMPATIBILITY OF BROADBAND AND NARROWBAND SHORTWAVE RADIO COMMUNICATIONS DEVICES." Sciences of Europe, no. 158 (February 10, 2025): 78–86. https://doi.org/10.5281/zenodo.14846872.

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Most short-wave radio communication means use frequency modulation of the radio signal in a limited frequency band to transmit voice signals. Such signals have a sufficiently high spectral density, which makes it possible to detect and suppress the radio signal by means of electronic warfare. One of the methods for increasing the noise immunity of radio communication means is to expand the radio signal spectrum at the operating frequency of the transmitter. In modern telecommunication systems, various technologies for expanding the signal spectrum have been used when transmitting data over a m

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R., Suresh Kumar, and P.Manimegalai. "Detection and Separation of Eeg Artifacts Using Wavelet Transform." International Journal of Informatics and Communication Technology (IJ-ICT) 7, no. 3 (2018): 127–34. https://doi.org/10.11591/ijict.v7i3.pp127-134.

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Bio-medical signal processing is one of the most important techniques of multichannel sensor network and it has a substantial concentration in medical application. However, the real-time and recorded signals in multisensory instruments contains different and huge amount of noise, and great work has been completed in developing most favorable structures for estimating the signal source from the noisy signal in multichannel observations. Methods have been developed to obtain the optimal linear estimation of the output signal through the Wide-Sense-Stationary (WSS) process with the help of time-i

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Zhang, Mei Jun, Hao Chen, Chuang Wang, and Qing Cao. "Threshold Noise Reduction Research of Improved EEMD Method." Applied Mechanics and Materials 226-228 (November 2012): 237–40. http://dx.doi.org/10.4028/www.scientific.net/amm.226-228.237.

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In order to extract effectively detection signals in the noise background for non-stationary signal.On the basis of EEMD, improved EEMD is put forward, the improve EEMD threshold noise reduction is researched in this paper.The simulation signal compared the noise reduction effect of the wavelet,EMD,EEMD,and the improved EEMD. The improved EEMD threshold noise reduction have the best noise reduction result , the highest signal-to-noise ratio, the smallest standard deviation error.After the improved EEMD threshold noise reduction , the measurement signal time domain waveform smooth. More high fr

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Zhang, Yatao, Shoushui Wei, Yutao Long, and Chengyu Liu. "Performance Analysis of Multiscale Entropy for the Assessment of ECG Signal Quality." Journal of Electrical and Computer Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/563915.

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This study explored the performance of multiscale entropy (MSE) for the assessment of mobile ECG signal quality, aiming to provide a reasonable application guideline. Firstly, the MSE for the typical noises, that is, high frequency (HF) noise, low frequency (LF) noise, and power-line (PL) noise, was analyzed. The sensitivity of MSE to the signal to noise ratio (SNR) of the synthetic artificial ECG plus different noises was further investigated. The results showed that the MSE values could reflect content level of various noises contained in the ECG signals. For the synthetic ECG plus LF noise,

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Grinev, E. M., V. P. Pashintsev, and Yu I. Galushko. "Determination of frequency dependencies of deciles of the signal-to-noise ratio." Sovremennaya nauka i innovatsii, no. 4 (44) (2023): 25–31. http://dx.doi.org/10.37493/2307-910x.2023.4.3.

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The level of signal and interference in the decameter range of radio waves is subject to significant random changes, which affects the reliability of radio communications. The reliability of radio communication in the decameter range is determined by the ratio of the average signal level to the noise level at the receiver input to its permissible value, which, in turn, depends on the selected operating frequency. Also an important indicator is the standard deviation (standard deviation) of the signal-tonoise ratio at the receiver input. The latter is considered to be a constant value and is 14

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Bohachev, Ihor, Svitlana Kovtun, Yurii Kuts, Stanislav Sozonov, and Vladyslav Khaidurov. "Enhanced phase method of signal detection for ultrasonic magnetostriction defectoscopy of power equipment." System Research in Energy 2023, no. 2 (2023): 72–82. http://dx.doi.org/10.15407/srenergy2023.02.072.

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The magnetostrictive method of ultrasonic flaw detection has certain advantages, in particular, the ability to control objects with complex geometry, at their high temperature, the ability to control dry contact between the transducer and the object, difficult access to the controlled area, etc. The peculiarities of the generation of ultrasonic waves by magnetostrictive transducers and their distribution in control objects determine the low level of the signal/noise ratio, which limits the possibilities of practical application of this method. The aim of the paper is to improve the phase metho

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Sodickson, Daniel K., Mark A. Griswold, Peter M. Jakob, Robert R. Edelman, and Warren J. Manning. "Signal-to-noise ratio and signal-to-noise efficiency in SMASH imaging." Magnetic Resonance in Medicine 41, no. 5 (1999): 1009–22. http://dx.doi.org/10.1002/(sici)1522-2594(199905)41:5<1009::aid-mrm21>3.0.co;2-4.

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