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Artykuły w czasopismach na temat „Types of Noise”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Zayed, M. Ramadan. "Optimum Image Filters for Various Types of Noise." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 5 (2018): 2458–64. https://doi.org/10.12928/TELKOMNIKA.v16i5.10508.

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In this paper, the quality performance of several filters in restoration of images corrupted with various types of noise has been examined extensively. In particular, Wiener filter, Gaussian filter, median filter and averaging (mean) filter have been used to reduce Gaussian noise, speckle noise, salt and pepper noise and Poisson noise. Many images have been tested, two of which are shown in this paper. Several percentages of noise corrupting the images have been examined in the simulations. The size of the sliding window is the same in the four filters used, namely 5x5 for all the indicated no

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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 (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 noise

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3

Ayrbabamyan, S. A., and E. A. Bugarev. "Types of noise barriers." Izvestiya MGTU MAMI 7, no. 1-4 (2013): 134–38. http://dx.doi.org/10.17816/2074-0530-67851.

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Liu, Ying, Deying Gu, Huiling Zhao, and Rong Yu. "Influence of Different Noise Types on Hearing Function in Patients Treated for Mild Otitis Media." Noise and Health 26, no. 121 (2024): 231–34. http://dx.doi.org/10.4103/nah.nah_6_24.

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Background: Otitis media (OM) refers to a common clinical ear disease. Noise seriously damages human hearing function. This study aimed to investigate the effects of various noise types on the hearing function of patients who have recovered from mild OM. Materials and Methods: A total of 160 patients with mild OM treated at our hospital from May 2020 to May 2023 were retrospectively selected for this study. Based on clinical data, the patients were divided into the non-noise group (n = 80) and the noise (n = 80) group. The hearing thresholds of the two groups were compared across various noise

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Hecht, Markus, Thilo Hanisch, Anastasia Ullrich, et al. "Effects of Locomotive Noise Reduction to Freight Train Noise in Switzerland and Europe." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 8 (2023): 586–92. http://dx.doi.org/10.3397/in_2023_0097.

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As freight trains are very frequently operated at night there is still big concern about freight train noise in Europe. Freight wagons in Switzerland and Germany are now all equipped with composite brake blocks instead of cast iron brake blocks which results in significant noise reductions. Using data from the Swiss noise monitoring stations the contribution of different locomotives to the overall train noise was evaluated. For locomotive types without cast iron brake blocks the year of construction is not related to the noise behavior. Newer types are not in general less noisy than old ones.

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6

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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7

Nageswara Rao, S., K. Jaya Sankar, and C. D. Naidu. "An Improved Bi-Level Thresholding Based Uncertainty Evaluation for Speech Enhancement in Non-Stationary Noises." International Journal of Engineering & Technology 7, no. 2.24 (2018): 436. http://dx.doi.org/10.14419/ijet.v7i2.24.12130.

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This paper proposes a new speech enhancement framework to improve the quality of speeches recorded under adverse acoustic environments based on the speech presence uncertainty. Since the uncertainty evaluation gives a more and clear discrimination about the speech and noise, this paper proposes a new uncertainty evaluation mechanism as a preprocessing mechanism to the noise suppression methods. This mechanism relates with energies of a noisy speech signal and classifies the speech segments and noise segments more perfectly. In addition to the quality enhancement, this approach also reduces the

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8

Zhang, Lu, Mingjiang Wang, Qiquan Zhang, and Ming Liu. "Environmental Attention-Guided Branchy Neural Network for Speech Enhancement." Applied Sciences 10, no. 3 (2020): 1167. http://dx.doi.org/10.3390/app10031167.

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The performance of speech enhancement algorithms can be further improved by considering the application scenarios of speech products. In this paper, we propose an attention-based branchy neural network framework by incorporating the prior environmental information for noise reduction. In the whole denoising framework, first, an environment classification network is trained to distinguish the noise type of each noisy speech frame. Guided by this classification network, the denoising network gradually learns respective noise reduction abilities in different branches. Unlike most deep neural netw

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9

Rhebergen, Koenraad S., and Wouter A. Dreschler. "The extended speech reception threshold model: Predicting speech intelligibility in different types of non-stationary noise in hearing-impaired listeners." Journal of the Acoustical Society of America 157, no. 2 (2025): 1500–1511. https://doi.org/10.1121/10.0035833.

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The speech reception threshold (SRT) model of Plomp [J. Acoust. Soc. Am. 63(2), 533–549 (1978)] can be used to describe SRT (dB signal-to-noise ratio) for 50% of sentences correct in stationary noise in normal-hearing (NH) and hearing-impaired (HI) listeners. The extended speech reception threshold model (ESRT) [Rhebergen et al., J. Acoust. Soc. Am. 117, 2181–2192 (2010)] was introduced to describe the SRT in non-stationary noises. With the ESRT model, they showed that the SRT in non-stationary noises is, contra to the SRT in stationary noise, dependent on the non-stationary noise type and noi

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10

Brochier, Tim J., Amanda Fullerton, Adam Hersbach, Harish Krishnamoorthi, and Zachary Smith. "Deep neural network-based speech enhancement for cochlear implants." Journal of the Acoustical Society of America 154, no. 4_supplement (2023): A28. http://dx.doi.org/10.1121/10.0022678.

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Noisy conditions make understanding speech with a cochlear implant (CI) difficult. Speech enhancement (SE) algorithms based on signal statistics can be beneficial in stationary noise, but rarely provide benefit in modulated multi-talker babble. Current approaches using deep neural networks (DNNs) rely on a data driven approach for training and promise improvements in a wide variety of noisy conditions. In this study a DNN-based SE algorithm was evaluated in CI listeners. The network was trained on a large database of publicly available recordings. A double-blinded acute evaluation was conducte

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11

Chai, Yuying, and Boya Yu. "Effect of rail traffic noises on the perception of the acoustic environment in office spaces." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 6 (2023): 2324–32. http://dx.doi.org/10.3397/in_2023_0342.

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This study conducted a laboratory experiment to investigate the effect of rail traffic noise on the perception of the acoustic environment in office spaces. The study considered two types of experiment stimuli, single noise, and combined noise. The single noise stimuli consisted of silence (SL), air conditioning noise (AC), irrelevant speech (SP), and six types of traffic noise (Tr). Traffic noise included road (R), maglev (Ma), tram (T), conventional train (C), high-speed train (H), and metro (Me). The combined noise stimuli used air conditioning sound and speech as background noise and combi

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12

Lundberg, Emily M. H., Song Hui Chon, James M. Kates, Melinda C. Anderson, and Kathryn H. Arehart. "The Type of Noise Influences Quality Ratings for Noisy Speech in Hearing Aid Users." Journal of Speech, Language, and Hearing Research 63, no. 12 (2020): 4300–4313. http://dx.doi.org/10.1044/2020_jslhr-20-00156.

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Purpose The overall goal of the current study was to determine whether noise type plays a role in perceptual quality ratings. We compared quality ratings using various noise types and signal-to-noise ratio (SNR) ranges using hearing aid simulations to consider the effects of hearing aid processing features. Method Ten older adults with bilateral mild to moderately severe sensorineural hearing loss rated the sound quality of sentences processed through a hearing aid simulation and presented in the presence of five different noise types (six-talker babble, three-talker conversation, street traff

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13

Alokaily, Ahmad O., Abdulaziz F. Alqabbani, Adham Aleid, and Khalid Alhussaini. "Toward Accessible Hearing Care: The Development of a Versatile Arabic Word-in-Noise Screening Tool: A Pilot Study." Applied Sciences 12, no. 23 (2022): 12459. http://dx.doi.org/10.3390/app122312459.

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Speech-in-noise tests are used to assess the ability of the human auditory system to perceive speech in a noisy environment. Early diagnosis of hearing deficits helps health professionals to plan for the most appropriate management. However, hospitals and auditory clinics have a shortage of reliable Arabic versions of speech-in-noise tests. Additionally, access to specialized healthcare facilities is associated with socioeconomic status. Hence, individuals with compromised socioeconomic status do not have proper access to healthcare. Thus, In the current study, a mobile and cost-effective Arab

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14

Mohanty, Sumant Sekhar, and Sushreeta Tripathy. "Application of Different Filtering Techniques in Digital Image Processing." Journal of Physics: Conference Series 2062, no. 1 (2021): 012007. http://dx.doi.org/10.1088/1742-6596/2062/1/012007.

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Abstract Noise in an image is a random variation of brightness or color information in the original image. Noise is consistently presented in digital images during picture obtaining, coding, transmission, and processing steps. Image noise is most apparent in image regions with a low signal level. There are various reasons for the creation of noise in an image, such as electronic noise in amplifiers or detectors, disturbances and overheating of the sensor, disturbances in the medium of traveling for a digital image, etc. Noise is exceptionally hard to eliminate from the digital pictures without

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15

JENSEN, KRISTOFFER. "Atomic noise." Organised Sound 10, no. 1 (2005): 75–81. http://dx.doi.org/10.1017/s1355771805000695.

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Stochastic, unvoiced sounds are abundant in music and musical sounds. Without irregularities, the music and sounds become dull and lifeless. This paper presents work on unvoiced sounds that is believed to be useful in noise music. Several methods for obtaining a gradual change towards static white noise are presented. The random values (Dice), random events (Geiger) and random frequencies (Cymbal) noise types are shown to produce many useful sounds. Atomic noise encompasses all three noise types, while adding much more subtle variations and more life to the noise. Methods for obtaining a harmo

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16

Alabbasi, Hesham A., Ali M. Jalil, and Fadhil S. Hasan. "Adaptive wavelet thresholding with robust hybrid features for text-independent speaker identification system." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (2020): 5208. http://dx.doi.org/10.11591/ijece.v10i5.pp5208-5216.

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The robustness of speaker identification system over additive noise channel is crucial for real-world applications. In speaker identification (SID) systems, the extracted features from each speech frame are an essential factor for building a reliable identification system. For clean environments, the identification system works well; in noisy environments, there is an additive noise, which is affect the system. To eliminate the problem of additive noise and to achieve a high accuracy in speaker identification system a proposed algorithm for feature extraction based on speech enhancement and a

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Hesham, A. Alabbasi, M. Jalil Ali, and S. Hasan Fadhil. "Adaptive wavelet thresholding with robust hybrid features for text-independent speaker identification system." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (2020): 5208–16. https://doi.org/10.11591/ijece.v10i5.pp5208-5216.

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The robustness of speaker identification system over additive noise channel is crucial for real-world applications. In speaker identification (SID) systems, the extracted features from each speech frame are an essential factor for building a reliable identification system. For clean environments, the identification system works well; in noisy environments, there is an additive noise, which is affect the system. To eliminate the problem of additive noise and to achieve a high accuracy in speaker identification system a proposed algorithm for feature extraction based on speech enhancement and a

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18

Goyal, Bhawna, Ayush Dogra, Sunil Agrawal, and B. S. Sohi. "Noise Issues Prevailing in Various Types of Medical Images." Biomedical and Pharmacology Journal 11, no. 3 (2018): 1227–37. http://dx.doi.org/10.13005/bpj/1484.

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The current literature documents a plethora of image denoising techniques in the fields of medical imaging, remote sensing, biometrics, surveillance and vegetation mapping. Therefore it is important to have brief insight into various types of noises in different type of images, for instance medical images, remote sensing images and natural images. This article encompasses the basic definition, history, usage and type of noise affecting some of the major types of imaging modalities. Besides this a brief discussion on the type of noise prevailing in remote sensing and natural images is also give

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19

Ali, Suhad A., C. Elaf A. Abbood, and Shaymaa Abdu LKadhm. "Salt and Pepper Noise Removal Using Resizable Window and Gaussian Estimation Function." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (2016): 2219. http://dx.doi.org/10.11591/ijece.v6i5.11641.

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<p class="Default">Most types of the images are corrupted in many ways that because exposed to different types of noises. The corruptions happen during transmission from space to another, during storing or capturing. Image processing has various techniques to process the image. Before process the image, there is need to remove noise that corrupt the image and enhance it to be as near as to the original image. This paper proposed a new method to process a particular common type of noise. This method removes salt and pepper noise by using many techniques. First, detect the noisy pixel, the

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20

Ali, Suhad A., C. Elaf A. Abbood, and Shaymaa Abdu LKadhm. "Salt and Pepper Noise Removal Using Resizable Window and Gaussian Estimation Function." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (2016): 2219. http://dx.doi.org/10.11591/ijece.v6i5.pp2219-2224.

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<p class="Default">Most types of the images are corrupted in many ways that because exposed to different types of noises. The corruptions happen during transmission from space to another, during storing or capturing. Image processing has various techniques to process the image. Before process the image, there is need to remove noise that corrupt the image and enhance it to be as near as to the original image. This paper proposed a new method to process a particular common type of noise. This method removes salt and pepper noise by using many techniques. First, detect the noisy pixel, the

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21

Lokhande, Narendra Lalchand, and Tushar Hrishikesh Jaware. "Effective CT Lung Image Denoising using Deep-Dense Inception Generative Adversarial Network." International Research Journal of Multidisciplinary Scope 06, no. 01 (2025): 867–78. https://doi.org/10.47857/irjms.2025.v06i01.02856.

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Computed tomography (CT) is used to visualize body structures and diagnose anomalies, making it an important tool in medical diagnosis and therapy planning. However, imaging techniques such as CT, MRI, ultrasound (US), and PET are frequently hampered by numerous types of noise, including Gaussian, speckle, Poisson variability, and salt-andpepper disturbances. These noises are created by technological interference, image processing flaws, and patient movement, which reduce image clarity and conceal key diagnostic details. The major difficulty in medical imaging is to remove noise while retainin

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Tian, Wen-Qiang, Dan Gao, Ju-Feng Luo, Wei-Yi Zhang, and Ying-Guan Wang. "Effect of different types of noises on the formations of swarming systems: the sensing-noise and the acting-noise." Modern Physics Letters B 28, no. 23 (2014): 1450186. http://dx.doi.org/10.1142/s0217984914501863.

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In this paper, different types of noises, the sensing-noise and the acting-noise, are brought into the extended adaptive Attractive/Repulsive (A/R) swarming models to explore the role of noise in swarming formations. The difference between these two extended A/R models consists in the way in which the noise is introduced. The sensing-noise is added to the inputs of the swarming system which results in the uncertainty of the sensed information for agents, and it affects the whole processes of the swarming system. The acting-noise is added to the outputs of the swarming system, which does not af

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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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Kwon, Ju Hyeok, So Eui Kim, Na Hye Kim, Eui Chul Lee, and Jee Hang Lee. "Preeminently Robust Neural PPG Denoiser." Sensors 22, no. 6 (2022): 2082. http://dx.doi.org/10.3390/s22062082.

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Photoplethysmography (PPG) is a simple and cost-efficient technique that effectively measures cardiovascular response by detecting blood volume changes in a noninvasive manner. A practical challenge in the use of PPGs in real-world applications is noise reduction. PPG signals are likely to be compromised by various types of noise, such as scattering or motion artifacts, and removing such compounding noises using a monotonous method is not easy. To this end, this paper proposes a neural PPG denoiser that can robustly remove multiple types of noise from a PPG signal. By casting the noise reducti

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GAO, J. B., C. C. CHEN, S. K. HWANG, and J. M. LIU. "NOISE-INDUCED CHAOS." International Journal of Modern Physics B 13, no. 28 (1999): 3283–305. http://dx.doi.org/10.1142/s0217979299003027.

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Noise-induced chaos is an interesting phenomenon. However, it is a subtle issue because of the difficulty in distinguishing between true low-dimensional chaos and noise. In this review article, we consider how to define noise-induced chaos and what constitutes a test for noise-induced chaos. The mechanism for noise-induced chaos is studied by considering the long-term growth rate of the logarithmic displacement curves. In particular, we have identified three types of diffusional processes, with the third type, the anomalous diffusion, being the precursor of noise-induced chaos. A number of dyn

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Laxman, Singh, Kumar Chaudhary Sunil, Kumar Verma Yogesh, Kant Pratap Singh Yadav Jay, and Kumar Rajeev. "Smart Volume Controller for Mobile Phones." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 2 (2019): 256–59. https://doi.org/10.35940/ijeat.B2313.129219.

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In this paper, smart volume controller (SVC) using fuzzy logic is developed for mobile phones in order to improve the voice quality in the presence of background noise. The SVC uses the noise level and class information as an input to automatically raise the volume of the cell phone in the presence of background noise. Smart volume controller mainly consists of two stages: (i) Noise Classification, (ii) Fuzzy Volume Controller. Noise classification includes feature extraction and feature matching using artificial neural network classifier to differentiate between different types of noise class

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Ataeyan, Mahdieh, and Negin Daneshpour. "Automated Noise Detection in a Database Based on a Combined Method." Statistics, Optimization & Information Computing 9, no. 3 (2021): 665–80. http://dx.doi.org/10.19139/soic-2310-5070-879.

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Data quality has diverse dimensions, from which accuracy is the most important one. Data cleaning is one of the preprocessing steps in data mining which consists of detecting errors and repairing them. Noise is a common type of error, that occur in database. This paper proposes an automated method based on the k-means clustering for noise detection. At first, each attribute (Aj) is temporarily removed from data and the k-means clustering is applied to other attributes. Thereafter, the k-nearest neighbors is used in each cluster. After that a value is predicted for Aj in each record by the near

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Mandot, Manju, Shrusti Porwal, and Reena Gupta. "Overview on Noise, Types of Noises which Corrupts The Digital Images and The Lsh-Frequency Domain Filtering Technique to Remove Noise in Medical Ultrasound Image." International Journal of Scientific Research 3, no. 7 (2012): 96–99. http://dx.doi.org/10.15373/22778179/july2014/31.

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Zhang, Dunli. "Noise types and formation mechanism of machine vision." Advances in Engineering Technology Research 12, no. 1 (2024): 304. https://doi.org/10.56028/aetr.12.1.304.2024.

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Surface defect detection based on machine vision is more and more widely used in the industrial field. However, the noise in the image is inevitable, and the quality of filtering and denoising has a decisive impact on the success rate of subsequent defect recognition. This paper summarizes the causes and types of noise in machine vision images. This paper introduces three kinds of noise in detail, including Gaussian noise, Poisson noise and salt and pepper noise. The generation mechanism of the above three kinds of noise is analyzed and displayed in the detection image of electric vehicle magn

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Hao, Yiya, Shuai Cheng, Gong Chen, Yaobin Chen, and Liang Ruan. "A neural network based noise suppression method for transient noise control with low-complexity computation." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 1 (2021): 5902–9. http://dx.doi.org/10.3397/in-2021-11598.

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Over the decades, the noise-suppression (NS) methods for speech enhancement (SE) have been widely utilized, including the conventional signal processing methods and the deep neural networks (DNN) methods. Although stationary-noise can be suppressed successfully using conventional or DNN methods, it is significantly challenging while suppressing the non-stationary noise, especially the transient noise. Compared to conventional NS methods, DNN NS methods may work more effectively under non-stationary noises by learning the noises' temporal-frequency characteristics. However, most DNN methods are

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Lv, Li, та Ping Zhou. "Effect of noise on deterministic remote preparation of an arbitrary two-qudit state by using a four-qudit χ-type state as the quantum channel". International Journal of Quantum Information 18, № 05 (2020): 2050028. http://dx.doi.org/10.1142/s0219749920500288.

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We present a protocol for remote preparation of an arbitrary two-qudit state by using a four-qudit [Formula: see text]-type state as the quantum channel via positive operator-valued measurement. We first propose the protocol for remote preparation of an arbitrary two-qudit state via positive operator-valued measurement in noiseless environment and then discuss the protocol in noisy environments. Four important quantum decoherence noise models, the dephasing noise, the qudit-flip noise, the qudit-phase-flip noise and the depolarizing noise, are considered in our protocol. The output states and

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Al-Attabi, Ali, and Ali Al. "Spectral Graph Filtering for Noisy Signals Using the Kalman filter." ECTI Transactions on Electrical Engineering, Electronics, and Communications 21, no. 2 (2023): 249818. http://dx.doi.org/10.37936/ecti-eec.2023212.249818.

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Noise is unwanted electrical or electromagnetic radiation that degrades the quality of the signal and the data. It can be difficult to denoise a signal that has been acquired in a noisy environment, but doing so may be necessary in a number of signal processing applications. This paper extends the issue of signal denoising from signals with regular structures, which are affected by noise, to signals with irregular structures by applying the graph signal processing (GSP) technique and a very wellknown filter, the standard Kalman filter, after adjusting it. When the modified Kalman filter is com

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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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Feng, Jiahui, Tengtao Guo, Yuxuan Zhou, Xinyu Zhao, and Yan Xia. "Quantum coherence protection by utilizing hybrid noise." Laser Physics Letters 21, no. 10 (2024): 105203. http://dx.doi.org/10.1088/1612-202x/ad72d8.

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Abstract Noise is often considered as the biggest enemy of maintaining quantum coherence. However, in this paper, we show a scheme to protect quantum coherence by introducing extra noise. To be specific, we study an atom coupled to a single mode cavity (Jaynes–Cummings model) with two noises. One is from the cavity leakage, the other is from the stochastic atom-cavity coupling. Based on the non-Markovian dynamical equation, we show the quantum coherence can be protected by introducing the noise in the atom-cavity coupling. We study four different types of noises and show their performance on t

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Pan, Linchao, Can Gao, Jie Zhou, and Jinbao Wang. "Learning with Open-world Noisy Data via Class-independent Margin in Dual Representation Space." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 6 (2025): 6290–98. https://doi.org/10.1609/aaai.v39i6.32673.

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Learning with Noisy Labels (LNL) aims to improve the model generalization when facing data with noisy labels, and existing methods generally assume that noisy labels come from known classes, called closed-set noise. However, in real-world scenarios, noisy labels from similar unknown classes, i.e., open-set noise, may occur during the training and inference stage. Such open-world noisy labels may significantly impact the performance of LNL methods. In this study, we propose a novel dual-space joint learning method to robustly handle the open-world noise. To mitigate model overfitting on closed-

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Liu, Xiangxin, Zhengzhao Liang, Yanbo Zhang, Xianzhen Wu, and Zhiyi Liao. "Acoustic Emission Signal Recognition of Different Rocks Using Wavelet Transform and Artificial Neural Network." Shock and Vibration 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/846308.

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Different types of rocks generate acoustic emission (AE) signals with various frequencies and amplitudes. How to determine rock types by their AE characteristics in field monitoring is also useful to understand their mechanical behaviors. Different types of rock specimens (granulite, granite, limestone, and siltstone) were subjected to uniaxial compression until failure, and their AE signals were recorded during their fracturing process. The wavelet transform was used to decompose the AE signals, and the artificial neural network (ANN) was established to recognize the rock types and noise (art

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Yamakou, Marius E., and Tat Dat Tran. "Lévy noise-induced self-induced stochastic resonance in a memristive neuron." Nonlinear Dynamics 107, no. 3 (2021): 2847–65. http://dx.doi.org/10.1007/s11071-021-07088-6.

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AbstractAll previous studies on self-induced stochastic resonance (SISR) in neural systems have only considered the idealized Gaussian white noise. Moreover, these studies have ignored one electrophysiological aspect of the nerve cell: its memristive properties. In this paper, first, we show that in the excitable regime, the asymptotic matching of the deterministic timescale and mean escape timescale of an $$\alpha $$ α -stable Lévy process (with value increasing as a power $$\sigma ^{-\alpha }$$ σ - α of the noise amplitude $$\sigma $$ σ , unlike the mean escape timescale of a Gaussian proces

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Skurowski, Przemysław, and Magdalena Pawlyta. "On the Noise Complexity in an Optical Motion Capture Facility." Sensors 19, no. 20 (2019): 4435. http://dx.doi.org/10.3390/s19204435.

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Optical motion capture systems are state-of-the-art in motion acquisition; however, like any measurement system they are not error-free: noise is their intrinsic feature. The works so far mostly employ a simple noise model, expressing the uncertainty as a simple variance. In the work, we demonstrate that it might be not sufficient and we prove the existence of several types of noise and demonstrate how to quantify them using Allan variance. Such a knowledge is especially important for using optical motion capture to calibrate other techniques, and for applications requiring very fine quality o

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GUO, YANHUI, H. D. CHENG, and YINGTAO ZHANG. "A NEW NEUTROSOPHIC APPROACH TO IMAGE DENOISING." New Mathematics and Natural Computation 05, no. 03 (2009): 653–62. http://dx.doi.org/10.1142/s1793005709001490.

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A neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. The neutrosophic set is a general formal framework that has been recently proposed. However, the neutrosophic set needs to be specified from a technical point of view. Now, we apply the neutrosophic set into image domain and define some concepts and operators for image denoising. The image G is transformed into NS domain, which is described using three membership sets: T, I and F. The entropy of the neutrosophic set is de

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Sharma, Arvind Kumar, Avijit Majee, and Amrita Puri. "Study of filtered-x least mean square algorithm and its different variants for active noise control of complex real-world noises." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 5 (2023): 3851–62. http://dx.doi.org/10.3397/in_2023_0550.

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In various simulation studies for active noise control, noises are taken as tonal, multi-tonal, random broadband, and simulated chaotic noise. In reality, noises from real machines combine all these types of noises and background noise. This paper presents a comparative analysis of filtered-x least means square, filtered-e least mean square, filtered-x recursive least mean square, filtered-u least mean square, and leaky FxLMS for active noise control. Experimentally recorded noises of Band saw, CNC, Compressor, and welding processes are utilized for the analysis. The analysis is carried out fo

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Rouis, Mohamed, Salim Sbaa, and Nasser Edinne Benhassine. "The effectiveness of the choice of criteria on the stationary and non-stationary noise removal in the phonocardiogram (PCG) signal using discrete wavelet transform." Biomedical Engineering / Biomedizinische Technik 65, no. 3 (2020): 353–66. http://dx.doi.org/10.1515/bmt-2019-0197.

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AbstractThe greatest problem with recording heart sounds is parasitic noise effects. A reasonable solution to reduce noise can be carried out by minimization of extraneous noises in the vicinity of the patient during recording, in addition to the methods of signal processing that must be effective in noisy environments. Wavelet transform has become an essential tool for many applications, but its effectiveness is influenced by main parameters. Determination of mother wavelet function and decomposition level (DL) are important key factors to demonstrate the advantages of wavelet denoising. So,

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Sahoo, Lokanath, Krushnendu Sundar Sahoo, and Nitish Kumar Nayak. "The effect of environmental noise on speech perception of individuals with sensorineural hearing loss: a prospective observational study." International Journal of Otorhinolaryngology and Head and Neck Surgery 6, no. 7 (2020): 1263. http://dx.doi.org/10.18203/issn.2454-5929.ijohns20202778.

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<p class="abstract"><strong>Background:</strong> This study was done to identify the effect that environmental noises have on speech perception of individual with sensorineural hearing loss. The objectives were to develop evidence-based approach to support the need for sophisticated technology and to choose the better one for daily listening purposes of Hearing-Impaired individual to obtain a speech perception score when environmental noises are used as competing signal.</p><p class="abstract"><strong>Methods:</strong> The study was executed in three p

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Cherukuru, Pavani, and Mumtaz Begum Mustafa. "CNN-based noise reduction for multi-channel speech enhancement system with discrete wavelet transform (DWT) preprocessing." PeerJ Computer Science 10 (February 28, 2024): e1901. http://dx.doi.org/10.7717/peerj-cs.1901.

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Speech enhancement algorithms are applied in multiple levels of enhancement to improve the quality of speech signals under noisy environments known as multi-channel speech enhancement (MCSE) systems. Numerous existing algorithms are used to filter noise in speech enhancement systems, which are typically employed as a pre-processor to reduce noise and improve speech quality. They may, however, be limited in performing well under low signal-to-noise ratio (SNR) situations. The speech devices are exposed to all kinds of environmental noises which may go up to a high-level frequency of noises. The

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Tamazin, Mohamed, Ahmed Gouda, and Mohamed Khedr. "Enhanced Automatic Speech Recognition System Based on Enhancing Power-Normalized Cepstral Coefficients." Applied Sciences 9, no. 10 (2019): 2166. http://dx.doi.org/10.3390/app9102166.

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Many new consumer applications are based on the use of automatic speech recognition (ASR) systems, such as voice command interfaces, speech-to-text applications, and data entry processes. Although ASR systems have remarkably improved in recent decades, the speech recognition system performance still significantly degrades in the presence of noisy environments. Developing a robust ASR system that can work in real-world noise and other acoustic distorting conditions is an attractive research topic. Many advanced algorithms have been developed in the literature to deal with this problem; most of

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Mirzaev, Akramjon, and Sanjar Zoteev. "Noise in Telecommunication: Different Types and Methods of dealing with Noise." Journal La Multiapp 1, no. 5 (2021): 25–27. http://dx.doi.org/10.37899/journallamultiapp.v1i5.275.

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This article discusses noise in telecommunications: different types and methods of dealing with noise. Noise is arguably a very hated problem because it can interfere with the quality of signal reception and also the reproduction of the signal that will be transmitted. Not only that, but noise can also limit the range of the system to a certain emission power and can affect the sensitivity and sensitivity of the reception signal. Even in some cases, noise can also result in a reduction in the bandwidth of a system. Of course, we've all felt how annoying the noise effect is. For example, when l

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Cai, Yun. "Minimization of the difference of Nuclear and Frobenius norms for noisy low rank matrix recovery." International Journal of Wavelets, Multiresolution and Information Processing 18, no. 02 (2019): 1950056. http://dx.doi.org/10.1142/s0219691319500565.

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This paper considers recovery of matrices that are low rank or approximately low rank from linear measurements corrupted with additive noise. We study minimization of the difference of Nuclear and Frobenius norms (abbreviated as [Formula: see text] norm) as a nonconvex and Lipschitz continuous metric for solving this noisy low rank matrix recovery problem. We mainly study two types of bounded observation noisy low rank matrix recovery problems, including the [Formula: see text]-norm bounded noise and the Dantizg Selector noise. Based on the matrix restricted isometry property (abbreviated as M

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Wang, Ming-Ming, Zhi-Guo Qu, Wei Wang, and Jin-Guang Chen. "Effect of noise on joint remote preparation of multi-qubit state." International Journal of Quantum Information 15, no. 02 (2017): 1750012. http://dx.doi.org/10.1142/s0219749917500125.

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Quantum noise severely affects the security and reliability of quantum communication system. In this paper, we study the effect of quantum noise on quantum multiparty communication protocols. Taking a two-qubit joint remote state preparation (JRSP) scheme as an example, we point out that there are some calculation mistakes in a former JRSP scheme [X.W. Guan, X.B. Chen, L.C. Wang and Y.X. Yang, Int. J. Theor. Phys. 53(4) (2014) 2236.]. The revised output states and fidelities in two types of noise are presented, respectively. More importantly, we present a more general form for describing the e

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Sriwong, Kittipat, Kittisak Kerdprasop, and Nittaya Kerdprasop. "The Study of Noise Effect on CNN-Based Deep Learning from Medical Images." International Journal of Machine Learning and Computing 11, no. 3 (2021): 202–7. http://dx.doi.org/10.18178/ijmlc.2021.11.3.1036.

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Currently, computational modeling methods based on machine learning techniques in medical imaging are gaining more and more interests from health science researchers and practitioners. The high interest is due to efficiency of modern algorithms such as convolutional neural networks (CNN) and other types of deep learning. CNN is the most popular deep learning algorithm because of its prominent capability on learning key features from images that help capturing the correct class of images. Moreover, several sophisticated CNN architectures with many learning layers are available in the cloud comp

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Lee, Jaiyeop, Ilho Kim, and Seoil Chang. "Analysis of highway reflection noise reduction using transparent noise barrier types." Environmental Engineering Research 20, no. 4 (2015): 383–91. http://dx.doi.org/10.4491/eer.2015.065.

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Batho, Lauren P., Rhonda Martinussen, and Judith Wiener. "The Effects of Different Types of Environmental Noise on Academic Performance and Perceived Task Difficulty in Adolescents With ADHD." Journal of Attention Disorders 24, no. 8 (2015): 1181–91. http://dx.doi.org/10.1177/1087054715594421.

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Objective: To examine the effects of environmental noises (speech and white noise) relative to a no noise control condition on the performance and difficulty ratings of youth with ADHD ( N = 52) on academic tasks. Method: Reading performance was measured by an oral retell (reading accuracy) and the time spent reading. Writing performance was measured through the proportion of correct writing sequences (writing accuracy) and the total words written on an essay. Results: Participants in the white noise condition took less time to read the passage and wrote more words on the essay compared with p

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