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Academic literature on the topic 'Noise'

Author: Grafiati

Published: 4 June 2021

Last updated: 30 July 2024

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Journal articles on the topic "Noise"

1

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 ratio, preferable correlation coefficient and lower mean square error. Through analyzing these performance parameters and testing the denoising method using MIT-BIH Database, the conclusion can be drawn that the combination of EMD and adaptive noise cancellation has considered the frequency distribution of ECG and noises, eliminate the noises effectively and need not to select a proper threshold.

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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 (January 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 signals are de-noised using STFT techniques. Finally Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR) values for noised and de-noised signals are obtained.</p>

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Li, Yongsong, Zhengzhou Li, Kai Wei, Weiqi Xiong, Jiangpeng Yu, and Bo Qi. "Noise Estimation for Image Sensor Based on Local Entropy and Median Absolute Deviation." Sensors 19, no. 2 (January 16, 2019): 339. http://dx.doi.org/10.3390/s19020339.

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Noise estimation for image sensor is a key technique in many image pre-processing applications such as blind de-noising. The existing noise estimation methods for additive white Gaussian noise (AWGN) and Poisson-Gaussian noise (PGN) may underestimate or overestimate the noise level in the situation of a heavy textured scene image. To cope with this problem, a novel homogenous block-based noise estimation method is proposed to calculate these noises in this paper. Initially, the noisy image is transformed into the map of local gray statistic entropy (LGSE), and the weakly textured image blocks can be selected with several biggest LGSE values in a descending order. Then, the Haar wavelet-based local median absolute deviation (HLMAD) is presented to compute the local variance of these selected homogenous blocks. After that, the noise parameters can be estimated accurately by applying the maximum likelihood estimation (MLE) to analyze the local mean and variance of selected blocks. Extensive experiments on synthesized noised images are induced and the experimental results show that the proposed method could not only more accurately estimate the noise of various scene images with different noise levels than the compared state-of-the-art methods, but also promote the performance of the blind de-noising algorithm.

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Farshi, Taymaz Rahkar. "Image Noise Reduction Method Based on Compatibility with Adjacent Pixels." International Journal of Image and Graphics 17, no. 03 (July 2017): 1750014. http://dx.doi.org/10.1142/s0219467817500140.

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This paper proposes an efficient noise reduction method for gray and color images that are contaminated by salt-and-pepper noise. In the proposed method, the pixels that are more compatible with adjacent pixels are replaced with target (noisy) pixels. The algorithm is applied on noisy Lena and Mansion images that are contaminated by salt-and-pepper noise with 0.1 and 0.2 noise intensities. Although this method is developed for reducing noise from the images that are contaminated by salt-and-pepper noise, it can also reduce the noise from the images that are contaminated by other types of noises; yet it is more efficient for reducing salt-and-pepper noise. Both numerical and visual comparisons are demonstrated in the experimental simulations. The results show the proposed algorithm can successfully remove impulse noise from images that are contaminated by salt-and-pepper noise.

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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 (August 5, 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 transmitting. The procedure of the pure noise and the noisy MRS signal acquisition will be repeated several times. Then, the pure noise and the noisy signal are averaged to preliminarily suppress the noise. Secondly, the averaged pure noise and the noisy signal are divided into multiple frames. The framed signal is transformed into the frequency domain and the spectral subtraction method is applied to further suppress the electromagnetic noise embedded in the noisy MRS signal. Finally, the de-noised signal is recovered by the overlap-add method and inverse Fourier transformation. The approach was examined by numerical simulation and field measurements. After applying the proposed approach, the SNR of the MRS data was improved by 16.89 dB and both the random noise and the harmonic noise were well suppressed.

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Wang, Runjie, Wenzhong Shi, Xianglei Liu, and Zhiyuan Li. "An Adaptive Cutoff Frequency Selection Approach for Fast Fourier Transform Method and Its Application into Short-Term Traffic Flow Forecasting." ISPRS International Journal of Geo-Information 9, no. 12 (December 7, 2020): 731. http://dx.doi.org/10.3390/ijgi9120731.

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Historical measurements are usually used to build assimilation models in sequential data assimilation (S-DA) systems. However, they are always disturbed by local noises. Simultaneously, the accuracy of assimilation model construction and assimilation forecasting results will be affected. The fast Fourier transform (FFT) method can be used to acquire de-noised historical traffic flow measurements to reduce the influence of local noises on constructed assimilation models and improve the accuracy of assimilation results. In the practical signal de-noising applications, the FFT method is commonly used to de-noise the noisy signal with known noise frequency. However, knowing the noise frequency is difficult. Thus, a proper cutoff frequency should be chosen to separate high-frequency information caused by noises from the low-frequency part of useful signals under the unknown noise frequency. If the cutoff frequency is too high, too much noisy information will be treated as useful information. Conversely, if the cutoff frequency is too low, part of the useful information will be lost. To solve this problem, this paper proposes an adaptive cutoff frequency selection (A-CFS) method based on cross-validation. The proposed method can determine a proper cutoff frequency and ensure the quality of de-noised outputs for a given dataset using the FFT method without noise frequency information. Experimental results of real-world traffic flow data measurements in a sub-area of a highway near Birmingham, England, demonstrate the superior performance of the proposed A-CFS method in noisy information separation using the FFT method. The differences between true and predicted traffic flow values are evaluated using the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage (MAPE) values. Compared to the results of the two commonly used de-noising methods, i.e., discrete wavelet transform (DWT) and ensemble empirical mode decomposition (EEMD) methods, the short-term traffic flow forecasting results of the proposed A-CFS method are much more reliable. In terms of the MAE value, the average relative improvements of the assimilation model built using the proposed method are 19.26%, 3.47%, and 4.25%, compared to the model built using raw data, DWT method, and EEMD method, respectively; the corresponding average relative improvements in RMSE are 19.05%, 5.36%, and 3.02%, respectively; lastly, the corresponding average relative improvements in MAPE are 18.88%, 2.83%, and 2.28%, respectively. The test results show that the proposed method is effective in separating noises from historical measurements and can improve the accuracy of assimilation model construction and assimilation forecasting results.

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Lingamaiah Kurva, Naga, and S. Varadarajan. "Dual tree complex wavelet transform based image denoising for Kalpana satellite images." International Journal of Engineering & Technology 7, no. 3.29 (August 24, 2018): 269. http://dx.doi.org/10.14419/ijet.v7i3.29.18810.

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This paper presents a new algorithm to reduce the noise from Kalpana Satellite Images using Dual Tree Complex Wavelet Transform technique. Satellite Images are not simple photographs; they are pictorial representation of measured data. Interpretation of noisy raw data leads to wrong estimation of geophysical parameters such as precipitation, cloud information etc., hence there is a need to improve the raw data by reducing the noise for better analysis. The satellite images are normally affected by various noises. This paper mainly concentrates on reducing the Gaussian noise, Poisson noise and Salt & Pepper noise. Finally the performance of the DTCWT wavelet measures in terms of Peak Signal to Noise Ratio and Structural Similarity Index for both noisy & denoised Kalpana images.

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Wu, Xiao Hong, Bin Wu, and Jie Wen Zhao. "Noise Fuzzy Learning Vector Quantization." Key Engineering Materials 439-440 (June 2010): 367–71. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.367.

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Fuzzy learning vector quantization (FLVQ) benefits from using the membership values coming from fuzzy c-means (FCM) as learning rates and it overcomes several problems of learning vector quantization (LVQ). However, FLVQ is sensitive to noises because it is a FCM-based algorithm (FCM is sensitive to noises). Here, a new fuzzy learning vector quantization model, called noise fuzzy learning vector quantization (NFLVQ), is proposed to handle the noises sensitivity problem of FLVQ. NFLVQ integrates LVQ and generalized noise clustering (GNC), uses the membership values from GNC as learning rates and clusters data containing noisy data better than FLVQ. Experimental results show the better performances of NFLVQ.

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Oh, Soo Hee, and Kyoungwon Lee. "Aircraft Noise of Airport Community in Korea." Audiology and Speech Research 16, no. 1 (January 31, 2020): 1–10. http://dx.doi.org/10.21848/asr.200001.

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Aircraft noise is one of the serious environmental noises with the increased use of flight traffic. The purpose of this study is to understand aircraft noise levels of airport communities in Korea using baseline data for audiologic management. Aircraft noise levels were retrieved from the National Noise Information System every month between 2004 and 2018. We reviewed aircraft noise levels obtained from total of 111 airport communities across 14 airports. In order to understand aircraft noise levels of civil and military airports, the aircraft noise levels measured in civil and military airport communities compared with the noise levels from civil airport communities. The data showed average 71-73 weight equivalent continuous perceived noise level (WECPNL) for fifteen years across airport cities and the average noise levels did not increase over time between 2004 and 2018 years. The civil and military airports showed about 12 WECPNLs of increased noise levels compared to the civil airports. The most civil and military airport communities, including Gwangju, Gunsan, Daegu, Wonju, and Cheongju generated the maximum noise levels and ranked as the highest airport for aircraft noise levels. Although aircraft noise levels in airport communities were similar over the past decade, civil and military airports generated increased noised levels compared to civil airports due to jet plane noises and other military-related noises. Careful consideration is necessary to implement noise reduction policy for civil and military airport communities. Ongoing noise control, hearing monitoring, education, and relevant policies are required to improve the quality of life in the airport community residences.

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Zhang, Jiangbo, and Yiyi Zhao. "The Robust Consensus of a Noisy Deffuant-Weisbuch Model." Mathematical Problems in Engineering 2018 (December 30, 2018): 1–10. http://dx.doi.org/10.1155/2018/1065451.

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We construct a new opinion formation of the Deffuant-Weisbuch model with the interference of the outer noise, where there are finite n agents and the evolution is discrete-time. The opinion interaction occurs by one randomly chosen pair at each time step. The difference to the original Deffuant-Weisbuch model is that communications of any selected pairs will be affected by noises. The aim of this paper is to study the robust consensus of this noisy Deffuant-Weisbuch model. We first define the noise strength as the maximum noise absolute value. We will then show that when the noise strength is less than a certain threshold, this noisy model will achieve T-robust consensus when t is sufficiently large; next we prove that the noisy model achieves robust consensus with a positive probability; finally, we demonstrate these results and provide numerical relations among the noise strength and some model parameters.

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Dissertations / Theses on the topic "Noise"

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NAKAGAWA, Seiichi, Souta HAMAGUCHI, and Norihide KITAOKA. "Noisy Speech Recognition Based on Integration/Selection of Multiple Noise Suppression Methods Using Noise GMMs." Institute of Electronics, Information and Communication Engineers, 2008. http://hdl.handle.net/2237/14965.

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Gisel, Christoph. "Noise pod : the need for urban noise." Thesis, Konstfack, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-25.

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This project is about the thought that urban noise is more needed than we may think. A lot of people can be really disturbed and upset about a noisy environment surrounding them. I want to show with this noise pod, a space where you can sit/lay while listening to everyday urban noise compositions, that noise can be really relaxing and enjoyable. Relaxation does not only come from the right choice of noise at the right time it also depends on the environment that you enjoy the soundscape in. This pod - a small capsule of space - is a place to sit by yourself, choose a noise composition and listen to it reflectivity. Compleatly insulated from the surrounding noise world, you will be able to enjoy the noise wich is supported with an interactive light installation. Escape from the noise you are disturbed by, through listening to the noise you like.

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Klein, Achim. "Annoyance indicators for various urban road vehicle pass-by noises and urban road traffic noise combined with tramway noise." Thesis, Vaulx-en-Velin, Ecole nationale des travaux publics, 2015. http://www.theses.fr/2015ENTP0002/document.

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La pollution sonore est un problème majeur pour les résidents des zones urbaines. La directive Européenne 2002/49/CE impose aux états membres l’établissement de cartes de bruit. Ces dernières sont construites sur la base de l’indice énergétique Lden, également utilisé dans les relations dose-effet établies pour prédire la gêne. Toutefois, pour l’évaluation de la gêne due au bruit dans les zones urbaines, la pertinence de cet indice est souvent remise en question. En effet, de nombreuses études ont montré que les caractéristiques temporelles et spectrales des bruits environnementaux influencent aussi les réponses de gêne et ne sont pas prises en compte dans cet indice. Cette thèse vise à contribuer à l’amélioration de la caractérisation de la gêne due au bruit des véhicules routiers en ville. Elle est basée sur des expériences réalisées en laboratoire. Elle comprend deux parties principales. La première partie a comme objectif de progresser sur la caractérisation physique et perceptive du bruit des passages de divers véhicules routiers en milieu urbain tels que les bus, les deux-roues motorisés, les poids lourds et les véhicules légers. Une attention particulière a été portée sur la caractérisation de la gêne due aux deuxroues motorisés qui sont cités parmi les véhicules routiers les plus gênants et sont peu étudiés dans la littérature. Dans cette perspective, un indicateur acoustique caractéristique de la gêne due au bruit routier urbain a été déterminé : il rend compte de différents attributs auditifs gênants en associant la sonie, un indice spectral et deux indices de modulation proposés dans le cadre de ces travaux. Dans les zones urbaines, les riverains sont souvent exposés à la circulation routière en présence d’autres sources de bruit de l’environnement. L’objectif principal de la deuxième partie est la prédiction de la gêne totale due au bruit du trafic routier urbain combiné avec le bruit de tramway. Dans le but de caractériser la gêne totale, les phénomènes perceptifs liés à la combinaison de ces bruits sont tout d’abord étudiés. Ensuite, l’indicateur proposé précédemment pour caractériser la gêne due au bruit des passages de différents véhicules routiers est testé lorsque différents trafics routiers urbains sont considérés. Sur la base de ces résultats, des modèles permettant de caractériser la gêne due au bruit de trafic routier urbain combiné au bruit de tramway ont été proposés
Noise pollution is a major concern for residents of urban areas. To date, the European directive 2002/49/CE requires member states to represent community noise through noise maps. These are produced using the Lden (day-evening-night level) index which is also employed for dose-effect relationships in noise annoyance prediction. However, for the assessment of noise annoyance in urban areas, its relevance is often questioned. Numerous studies have shown that noise annoyance due to community noise is not solely based on the sound pressure level and other acoustical signal characteristics such as temporal and spectral features influence noise annoyance ratings. This thesis aims to improve the assessment of noise annoyance due to various road vehicle noises in cities. It is based on experiments carried out in laboratory conditions and comprises two main parts. The first addresses the enhancement of the physical and perceptual characterization of annoyance due to various urban road vehicle pass-by noises, such as buses, poweredtwo- wheelers, heavy vehicles and light vehicles. A specific focus is put on the characterization of annoyance due to powered-two-wheelers which are among the most annoying road vehicles and studied little in the existing literature. An indicator accounting for annoyance-relevant auditory attributes of urban road vehicle pass-by noises is determined: it comprises loudness, a spectral index and two modulation indices proposed in this work. In urban agglomerations, people are often exposed to road traffic in presence of a variety of other environmental noise sources. The focal point of the second part is on the prediction of total annoyance due to urban road traffic noise combined with tramway noise. In the aim of adequately characterizing total annoyance, first the perceptual phenomena involved in annoyance due to the combination of the sources are studied. Furthermore, the analysis allows for the testing of the proposed noise annoyance indicator for the characterization of urban road traffic noise. To characterize annoyance due to tramway noise, an indicator determined in a recent study is employed. Based on these indicators and the findings regarding perceptual phenomena, models for the prediction of total annoyance due to combined urban road traffic and tramway noise are proposed

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Kaymak, Erkan. "Noise reduction and active noise control of high frequency narrow band dental drill noise." Thesis, Brunel University, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445923.

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Reschikoff, S. E. "Advanced Noise Generator Method of Flicker Noise Measurement." Thesis, Sumy State University, 2015. http://essuir.sumdu.edu.ua/handle/123456789/40983.

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Noise of electronic devices can be measured by comparison using a noise source at input and an output noise meter. It is noise generator method. It can be used to easily obtaining equivalent input noise of semiconductor devices. But this method is usually recommended for higher frequencies, because measurement generator must give white noise. Besides this, we obtain only noise level at broad band.

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Cochachin, Henostroza Franklin Rafael. "Noise-against-Noise Decoders : Low Precision Iterative Decoders." Thesis, Lorient, 2019. http://www.theses.fr/2019LORIS527.

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Dans cette thèse, deux décodeurs améliorés sont définis en utilisant un canal d’entrée quantifié avec seulement 3 ou 4 bits de précision pour les codes low-density parity-check (LDPC). Un algorithme de post-traitement pour les décodeurs itératifs de faible précision est également proposé. L'un des décodeurs proposés, appelé décodeur Noise-Against-Noise Min-Sum (NAN- MS), intègre une certaine quantité de perturbations aléatoires dues à une injection délibérée de bruit. L'autre des décodeurs proposés, appelé décodeur Sign-Preserving Min-Sum (SP-MS), conserve toujours le signe des messages et utilise toutes les combinaisons possibles pouvant être générées pour une précision donnée. De plus, le décodeur SP-MS peut réduire la précision de ses messages d'un bit tout en maintenant les mêmes performances de correction d'erreur. Le décodeur NAN-MS et le décodeur SP-MS présentent un gain de SNR pouvant atteindre 0,43 dB dans la région du waterfall de la courbe de performances. D'autre part, l'algorithme de post- processing proposé est très efficace et facilement adaptable aux décodeurs de faible précision. Pour le code IEEE ETHERNET, l'algorithme de post-processing implémenté dans un décodeur SP- MS de très faible précision permet de réduire le niveau d'erreur au-dessous d'un FER de 10-10. Sur un ASIC en technologie 28nm, une architecture entièrement parallèle du décodeur peut être mis en place sur une surface de 1.76 mm2, avec un débit de décodage de 319.34 Gbit/s et une efficacité matérielle de 181.44 Gbit/s/mm2
In this thesis, two improved decoders are defined using quantized input channel with only 3 or 4 bits of precision for low-density parity-check (LDPC) codes. Also, a post-processing algorithm for low precision iterative decoders is proposed. One of the proposed decoders, named Noise- Against-Noise Min-Sum (NAN-MS) decoder, incorporates a certain amount of random perturbation due to deliberate noise injection. The other of the proposed decoders, named Sign- Preserving Min-Sum (SP-MS) decoder, always preserve the sign of the messages and it uses all the possible combinations that can be generated for a given precision. Also, the SP-MS decoder can reduce the precision of its messages by one bit maintaining the same error correcting performance. The NAN-MS decoder and the SP-MS decoder present a SNR gain up to 0.43 dB the waterfall region of the performance curve. On the other hand, the proposed post-processing algorithm is very efficient and easily adaptable in low precision decoders. For the IEEE ETHERNET code, the post-processing algorithm implemented in a very low precision SP-MS decoder helps to lower the error floor below a FER of 10-10. On an ASIC of 28 nm of technology, the implementation results of a fully parallel architecture produces an area consumed by the decoder of 1.76 mm2, a decoding throughput of 319.34 Gbit/s, and a hardware efficiency of 181.44 Gbit/s/mm2

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Johnston, Adam Michael. "Noise Exposure System for Noise-Induced Hearing Loss." OpenSIUC, 2012. https://opensiuc.lib.siu.edu/theses/794.

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There is an estimated 10 million Americans that suffer from permanent, irreversible hearing loss from their workplace. Many soldiers come back from battle with this damage, mainly from the high sound levels of their weapons that they are exposed to. The U.S. government spends over $250 million a year in compensation to those whose hearing has been damaged. There are current medicines that have proven to help eliminate or lessen the affects from certain types of noise induced hearing loss, specifically from prolonged expose. A noise exposure system was needed to be built for impulse noise induced hearing loss testing. That would help lead to a medicine for impulse noise induced hearing loss. A system was designed and built to replicate the noise signal of an M-16 rifle. The system's digital noise signal produced was comparable to the recorded M-16 noise signal, which reached a 145 dB level. Testing showed that the relationship between the amplitude and the maximum levels measured were linear. Sound levels of the produced impulse waves had a maximum limit of approximately 160 dB. The system was designed with the idea of customization. There are multiple parameters that can be adjusted to best fit the testing needs. The noise exposure system will be used by researchers in the SIU school of medicine in research designed to test the effect. The results from Dr. the research will validate the effectiveness of the noise exposure system that was built.

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Gualandi, Nicola <1978&gt. "Aircraft noise performance evaluation and airport noise management." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1356/1/Gualandi_Nicola_Aircraft_noise_performance_evaluation_and_airport_noise_management.pdf.

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Gualandi, Nicola <1978&gt. "Aircraft noise performance evaluation and airport noise management." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1356/.

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Robert, Rene Jean. "Measuring noise level reduction using an artificial noise source." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54480.

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Buildings located near airports may be subjected to significant noise levels due to aircraft flyovers. Aircraft noise is particularly annoying when compared to other traffic noises due to its intermittent nature. While noise control is typically performed at the source, sound insulation programs are in place to improve the acoustic performance of a residence affected by the flyovers. Noise Level Reduction (NLR) is a common metric used in the United States to determine whether a residence qualifies for such programs. Sound insulation programs are available to houses that have an indoor Day Night Average Sound Level (DNL) greater than 45 dBA. NLR is a single-number metric used to quantify the ability for a building or building element to reduce the transmission of external sound pressure levels generated by aircraft. In addition to determining whether a residence qualifies, NLR can be used to quantify the effectiveness of the modifications performed as a result of the sound insulation program. NLR measurements with a loudspeaker offer an alternative method to those performed with aircraft flyovers, offering flexibility to the consultants that perform these measurements in the field. The purpose of this research was to better understand and improve the loudspeaker test for measuring NLR, providing a resource to the aircraft noise industry. Testing was completed on a "test house" that was constructed on campus with construction methods typical of a mixed-humid climate. The angular dependency, repeatability, and reproducibility of NLR, among other factors, were evaluated with field measurements. Significant NLR variations were observed with changes in lateral and vertical angles of incidence.

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Books on the topic "Noise"

1

ill, James Kennon, ed. Noise! noise! noise! Houston, TX: Advance Pub., 2003.

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illustrator, James Kennon, ed. Noise! noise! noise! Houston: Advance Publishing, Inc., 2014.

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ill, Martin Bruce, and Waterford Institute, eds. Noise? What noise? Sunnyvale, Calif: Electronic Education, 2001.

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ill, James Kennon, ed. Noise! noise! noise! =: Ruido! Ruido! Ruido! Houston: Advance, 2008.

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Kudyahakudadirwe, Christopher. The big noise and other noises. Chitungwiza, Zimbabwe: Mwanaka Media and Publishing, 2018.

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Cowley, Joy. Noise. Bothell, WA: Wright Group, 1996.

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Project, Nuffield Working with Science. Noise. York: Published for the Nuffield-Chelsea Curriculum Trust by Longman Resources Unit, 1986.

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Rosenberg, M. R. Noise. Dugort, Achill Island, Co. Mayo, Ireland: Redfoxpress, 2012.

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Jones, Alex. Noise. London: Nick Hern Books, 1997.

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Russell, Smith. Noise. Erin, Ont: Porcupine's Quill, 1998.

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Book chapters on the topic "Noise"

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McMullan, R. "Noise." In Environmental Science in Building, 189–213. London: Macmillan Education UK, 1992. http://dx.doi.org/10.1007/978-1-349-22169-1_10.

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Elsner, James B., and Anastasios A. Tsonis. "Noise." In Singular Spectrum Analysis, 69–86. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-2514-8_6.

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Rouan, Daniel. "Noise." In Encyclopedia of Astrobiology, 1127. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11274-4_1068.

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Stephenson, Ian. "Noise." In Essential Series, 257–70. London: Springer London, 2003. http://dx.doi.org/10.1007/978-1-4471-3800-6_26.

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Yamada, Minoru. "Noise." In Springer Series in Optical Sciences, 157–96. Tokyo: Springer Japan, 2014. http://dx.doi.org/10.1007/978-4-431-54889-8_10.

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Kågeson, Per. "Noise." In Economy & Environment, 229–30. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5264-8_15.

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Tremblay, Pierre. "Noise Music Information Retrieval." In Noise in and as Music, 77–96. University of Huddersfield Press, 2013. http://dx.doi.org/10.5920/noise.05.

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Yeang, Chen-Pang. "Spread-Spectrum Communication." In Transforming Noise, 397–410. Oxford University PressOxford, 2023. http://dx.doi.org/10.1093/oso/9780198887768.003.0013.

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Abstract One of the first applications of the wartime and postwar informational studies of noise was the spread-spectrum technology that scrambled transmitted signals in a communication system for encryptive or antijamming purposes. These scrambled signals effectively “rode on” a noisy carrier. But how to generate a sufficiently noisy carrier and how to synchronize the transmitter and receiver in noise modulation became central problems. In chapter 13, we examine Mortimer Rogoff’s invention of a “noise wheel” at the International Telephone and Telegraph (ITT) Company and MIT Lincoln Laboratories researchers’ development of electronic correlators for their NOMAC spread-spectrum system. In these Cold War military technological projects, noise was transformed from an environmental plight into something useful, as it was turned into a source of diversity.

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Yuan, Fei, Panpan Xun, Wei Wang, and Shibin Su. "Bearing Fault Diagnosis Based on Auto-Encoder Combined with CNN." In Fuzzy Systems and Data Mining IX. IOS Press, 2023. http://dx.doi.org/10.3233/faia231039.

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To address the problem that traditional bearing fault diagnosis methods rely on professional knowledge and are tedious, this paper proposes an end-to-end CNN-based bearing fault diagnosis model to achieve automatic fault recognition. In addition, considering the problem that noise exists in the actual working conditions, a bearing fault diagnosis model based on Auto-encoder (AE) combined with CNN is proposed (AE-CNN). The noisy signal is coded and decoded by the designed AE, and the de-noised result is used as the input of the designed CNN to achieve the bearing fault diagnosis under noisy conditions. Experiments on CWRU have proved the effectiveness of the designed CNN and AE-CNN. The designed CNN achieves 99.83% fault diagnosis accuracy under noise-free condition. The AE-CNN achieves 97.14% fault diagnosis accuracy under –4db signal-to-noise ratio (SNR) noise condition, which is 2.31% higher than the CNN with the same noise, and compared with the results of other advanced methods, it has achieved competitive results.

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Thigpen, Benjamin, and Peter Ablinger. "Black Square and Bottle Rack: noise and noises." In Noise in and as Music, 1–9. University of Huddersfield Press, 2013. http://dx.doi.org/10.5920/noise.01.

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Conference papers on the topic "Noise"

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Gammaitoni, L., F. Cottone, I. Neri, H. Vocca, Massimo Macucci, and Giovanni Basso. "Noise Harvesting." In NOISE AND FLUCTUATIONS: 20th International Conference on Noice and Fluctuations (ICNF-2009). AIP, 2009. http://dx.doi.org/10.1063/1.3140558.

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KOMORI, Masato, Yasuo MIURA, Masato MIKAMI, and Naoya KOJIMA. "19 Separation of Combustion Noise using Transient Noise Generation Model." In Small Engine Technology Conference & Exposition. 10-2 Gobancho, Chiyoda-ku, Tokyo, Japan: Society of Automotive Engineers of Japan, 2002. http://dx.doi.org/10.4271/2002-32-1788.

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<div class="htmlview paragraph">In a running engine, various impacts are excitation sources for structural vibrations and engine noises. Engine noises are classified, depending on their excitation sources, into the combustion noise, the combustion induced mechanical noise and the mechanical noise. It is difficult to measure such noises separately because some impacts occur closely in time and space. In this paper, a transient noise generation model of an engine was proposed considering vibration and its damping of engine structure. The present model was verified through the single explosion excitation experiment for a stationary engine. Using the noise generation model, the combustion noise was separated from the total noise radiating from a running four-stroke gasoline engine for motorcycles. It was found that the combustion noise had larger power at lower frequencies than higher frequencies. However, its contribution to the total engine noise was relatively small.</div>

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Xu, Cai, Yilin Zhang, Ziyu Guan, and Wei Zhao. "Trusted Multi-view Learning with Label Noise." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/582.

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Multi-view learning methods often focus on improving decision accuracy while neglecting the decision uncertainty, which significantly restricts their applications in safety-critical applications. To address this issue, researchers propose trusted multi-view methods that learn the class distribution for each instance, enabling the estimation of classification probabilities and uncertainty. However, these methods heavily rely on high-quality ground-truth labels. This motivates us to delve into a new generalized trusted multi-view learning problem: how to develop a reliable multi-view learning model under the guidance of noisy labels? We propose a trusted multi-view noise refining method to solve this problem. We first construct view-opinions using evidential deep neural networks, which consist of belief mass vectors and uncertainty estimates. Subsequently, we design view-specific noise correlation matrices that transform the original opinions into noisy opinions aligned with the noisy labels. Considering label noises originating from low-quality data features and easily-confused classes, we ensure that the diagonal elements of these matrices are inversely proportional to the uncertainty, while incorporating class relations into the off-diagonal elements. Finally, we aggregate the noisy opinions and employ a generalized maximum likelihood loss on the aggregated opinion for model training, guided by the noisy labels. We empirically compare TMNR with state-of-the-art trusted multi-view learning and label noise learning baselines on 5 publicly available datasets. Experiment results show that TMNR outperforms baseline methods on accuracy, reliability and robustness. The code and appendix are released at https://github.com/YilinZhang107/TMNR.

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Lin, Huangxing, Yihong Zhuang, Yue Huang, Xinghao Ding, Xiaoqing Liu, and Yizhou Yu. "Noise2Grad: Extract Image Noise to Denoise." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/115.

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In many image denoising tasks, the difficulty of collecting noisy/clean image pairs limits the application of supervised CNNs. We consider such a case in which paired data and noise statistics are not accessible, but unpaired noisy and clean images are easy to collect. To form the necessary supervision, our strategy is to extract the noise from the noisy image to synthesize new data. To ease the interference of the image background, we use a noise removal module to aid noise extraction. The noise removal module first roughly removes noise from the noisy image, which is equivalent to excluding much background information. A noise approximation module can therefore easily extract a new noise map from the removed noise to match the gradient of the noisy input. This noise map is added to a random clean image to synthesize a new data pair, which is then fed back to the noise removal module to correct the noise removal process. These two modules cooperate to extract noise finely. After convergence, the noise removal module can remove noise without damaging other background details, so we use it as our final denoising network. Experiments show that the denoising performance of the proposed method is competitive with other supervised CNNs.

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Chen, Hao, Pramod K. Varshney, and James H. Michels. "Denosing Noisy Images with Noise." In 2007 41st Asilomar conference on Signals, Systems and Computers (ACSSC). IEEE, 2007. http://dx.doi.org/10.1109/acssc.2007.4487265.

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Cannatà, G., G. Scandurra, C. Ciofi, Massimo Macucci, and Giovanni Basso. "A Very Simple Low Noise Voltage Preamplifier For High Sensitivity Noise Measurements." In NOISE AND FLUCTUATIONS: 20th International Conference on Noice and Fluctuations (ICNF-2009). AIP, 2009. http://dx.doi.org/10.1063/1.3140546.

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Vaks, V. L., A. N. Panin, S. I. Pripolzin, E. A. Sobakinskaya, D. G. Paveliev, Massimo Macucci, and Giovanni Basso. "Analysis Of Noise Characteristics And Noise Generation In SubTHz And THz Frequency Ranges." In NOISE AND FLUCTUATIONS: 20th International Conference on Noice and Fluctuations (ICNF-2009). AIP, 2009. http://dx.doi.org/10.1063/1.3140438.

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M, Jeba Jenitha, Kani Jesintha D, and Mahalakshmi P. "Noise Adaptive Fuzzy Switching Median Filters for Removing Gaussian Noise." In The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/ozsc7243/ngcesi23p113.

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Recently, in all image processing systems, image restoration plays a major role and it forms the major part of image processing systems. Medical images such as brain Magnetic Resonance Imaging (MRI), ultrasound images of liver and kidney, retinal images and images of uterus images are often affected by various types of noises such as Gaussian noise and salt and pepper noise. All image restoration techniques attempts to remove various types of noises. This paper deals with various filters namely Mean Filter, Averaging Filter, Median Filter, Adaptive Median Filter, Adaptive Weighted Median Filter, Gabor Filter and Noise Adaptive Fuzzy Switching Median Filter (NAFSM) for removing salt and pepper noise. Among all the filters, NAFSM removes the Gaussian noise better than the other filters and the performance of all the filters are compared using metrics such as PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), NAE (Normalized Absolute Error), Normalized Cross Correlation (NK), Average Difference (AD), Maximum Difference (MD), SC (Structural Content) and time elapsed to produce the denoised image.

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Xu, Yu-Yan, Yang Shen, Xiu-Shen Wei, and Jian Yang. "Webly-Supervised Fine-Grained Recognition with Partial Label Learning." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/209.

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The task of webly-supervised fine-grained recognition is to boost recognition accuracy of classifying subordinate categories (e.g., different bird species) by utilizing freely available but noisy web data. As the label noises significantly hurt the network training, it is desirable to distinguish and eliminate noisy images. In this paper, we propose two strategies, i.e., open-set noise removal and closed-set noise correction, to both remove such two kinds of web noises w.r.t. fine-grained recognition. Specifically, for open-set noise removal, we utilize a pre-trained deep model to perform deep descriptor transformation to estimate the positive correlation between these web images, and detect the open-set noises based on the correlation values. Regarding closed-set noise correction, we develop a top-k recall optimization loss for firstly assigning a label set towards each web image to reduce the impact of hard label assignment for closed-set noises. Then, we further propose to correct the sample with its label set as the true single label from a partial label learning perspective. Experiments on several webly-supervised fine-grained benchmark datasets show that our method obviously outperforms other existing state-of-the-art methods.

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BJORKMAN, M., and R. RYLANDER. "MAXIMUM NOISE LEVELS IN ROAD TRAFFIC NOISE." In Inter-Noise 1996. Institute of Acoustics, 2024. http://dx.doi.org/10.25144/19605.

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Reports on the topic "Noise"

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Deryabin, I. V. Noise-absorbing panel with bypass channels. FORGING AND STAMPING PRODUCTION. MATERIAL WORKING BY PRESSURE, August 2023. http://dx.doi.org/10.12731/kshpomd62023-deryabin.

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Noise, having a harmful effect on humans and the environment, forces us to search and conduct research on the development of new methods and means of noise protection. Currently, with an increasing increase in the flow of vehicles in residential areas, with the development of industrial production, the issue of noise control is becoming particularly relevant. A well-known and effective technical solution for blocking the transmission of acoustic energy is the use of noise-absorbing panels, both as part of various soundproof structures, and in the form of separate acoustic elements installed in noisy rooms. The article discusses the design of a noise-absorbing panel containing through bypass channels. Such a panel has a broadband sound absorption effect in frequency composition due to the use of porous sound-absorbing structures of structural materials with the integration of bypass channels into their composition.

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Doerry, Armin W. Noise and Noise Figure for Radar Receivers. Office of Scientific and Technical Information (OSTI), September 2016. http://dx.doi.org/10.2172/1562649.

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Mendel, Brock, and Andrei Shleifer. Chasing Noise. Cambridge, MA: National Bureau of Economic Research, May 2010. http://dx.doi.org/10.3386/w16042.

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Dow, James, and Gary Gorton. Noise Traders. Cambridge, MA: National Bureau of Economic Research, May 2006. http://dx.doi.org/10.3386/w12256.

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Jay. L51710 Active Noise Silencing. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 1994. http://dx.doi.org/10.55274/r0010333.

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Many natural gas compressor stations which were previously located away from residential areas are now being encroached upon by surrounding building developments. Furthermore, an increased awareness of community noise issues has proved to be the impetus for investigating and developing more effective noise control methods and treatments for natural gas compressor facilities. This project investigates the feasibility of applying Active Noise Cancellation (ANC) to the exhaust of a large, internal-combustion reciprocating type engine. Large reciprocating internal combustion engines pose significant challenges for the noise control engineer. In the case of the engines employed at Tennessee Gas Pipeline Company Compressor Station 229, these engines radiate extremely low frequency exhaust noise into the surrounding environs. These engines produce discrete frequencies in the exhaust spectra with a particularly strong component at 26.5 Hz, which corresponds to the fundamental firing frequency (the 5.0 rotational order) of the engine; significant attenuation of the raw exhaust noise can be particularly difficult due to the sound power and spectral content. Traditional methods would necessitate a very large silencer in order to realize improved attenuation of the exhaust noise, relative to the existing silencer. Measurements were conducted at the error microphone location, at 1.0 meter from the exhaust outlet and at the property line. At a distance of 1.0 meter the WNCT integrated active / passive silencer yielded 84.5 dBA (92.3 dBL) while the original equipment silencer yielded 92.7 dBA (98.8 dBL). Band-limited (DC - 200 Hz) measurements were taken at the error microphone location; control off (WNCT passive - only): 109.8 dBL overall, 107.7 dBL 26.5 Hz component. With control on (WNCT active + passive) at the same position overall noise was 99.7 dBL with the 26.5 Hz component reading 89.1 dBL. Far-field A-weighted reductions were inconclusive due to the presence of other contributing noise sources possessing similar noise characteristics. Flow resistance measurements indicated that back pressure had been reduced by 95% relative to the original equipment silencer through the use of the integrated WNCT active / passive silencer.

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Kuperman, W. A., and W. S. Hodgkiss. Tow-Ship Noise. Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada438454.

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Arrieta, Rudy, Connie Minish, Donal Myrick, and Larry McGlothlin. Residual Noise Environment. Fort Belvoir, VA: Defense Technical Information Center, December 1993. http://dx.doi.org/10.21236/ada406626.

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Ventura, John C. Reactor Noise Analysis,. Fort Belvoir, VA: Defense Technical Information Center, May 1995. http://dx.doi.org/10.21236/ada299061.

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DEPARTMENT OF DEFENSE WASHINGTON DC. DoD Noise Program. Fort Belvoir, VA: Defense Technical Information Center, November 2005. http://dx.doi.org/10.21236/ada574286.

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Andersson, Andres, and Michael Ladd. Fluidic Noise Shield. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada385559.

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