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Journal articles on the topic 'Noise'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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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

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2

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

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

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

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

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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 (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

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

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

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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 (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

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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 (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

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9

Oh, Soo Hee, and Kyoungwon Lee. "Aircraft Noise of Airport Community in Korea." Audiology and Speech Research 16, no. 1 (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 airpor

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10

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

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11

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 an

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Selvaraj, Poovarasan, and E. Chandra. "A variant of SWEMDH technique based on variational mode decomposition for speech enhancement." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 3 (2021): 299–308. http://dx.doi.org/10.3233/kes-210072.

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In Speech Enhancement (SE) techniques, the major challenging task is to suppress non-stationary noises including white noise in real-time application scenarios. Many techniques have been developed for enhancing the vocal signals; however, those were not effective for suppressing non-stationary noises very well. Also, those have high time and resource consumption. As a result, Sliding Window Empirical Mode Decomposition and Hurst (SWEMDH)-based SE method where the speech signal was decomposed into Intrinsic Mode Functions (IMFs) based on the sliding window and the noise factor in each IMF was c

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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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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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TAI, CHENG-CHI, CHIH-HSING CHANG, CHUAN-CHING TAN, TSUNG-WEN HUANG, and CHING-CHAU SU. "ADAPTIVE BEAMFORMER WITH COMBINATION OF SUBBAND FILTERING FOR HEARING-AID SYSTEMS BACKGROUND NOISE REDUCTION." Biomedical Engineering: Applications, Basis and Communications 14, no. 02 (2002): 55–66. http://dx.doi.org/10.4015/s1016237202000097.

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In this paper, we present a noise reduction technique for hearing-aid systems. The proposed algorithm adopted adaptive beamformer with combination of subband filtering technique. The structure of conventional hearing aids is relatively simple. They amplify ambient sounds that include speech signal as well as noise. Because noise and human speech signal are amplified at the same time, hearing-aid users can't clearly hear speech signal in noisy environment. The direction of sound can be used to discriminate speech signal from noise by combining adaptive noise canceller and adaptive beamformer. W

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Pan, Mei-Sen, Jing-Tian Tang, and Xiao-Li Yang. "A MODIFIED ADAPTIVE MEDIAN FILTER METHOD AND ITS APPLICATIONS IN MEDICAL IMAGES." Biomedical Engineering: Applications, Basis and Communications 22, no. 06 (2010): 489–96. http://dx.doi.org/10.4015/s1016237210002237.

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Since the medical image is usually corrupted by noise, the filter method is applied to remove the noise and improve the image quality. In this paper, a modified adaptive median filter method is proposed for filtering the medical images. When identifying noises, by selecting the maximum and the minimum gray values in the image as a criterion of judging the noise pixels, the probability that a nonnoise pixel is misjudged to be a noisy one is reduced, and the processing time for finding the maximum and minimum gray values in each local window is drastically decreased as well. When filtering the i

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17

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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18

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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19

ACEVEDO MOSQUEDA, M. E., M. A. ACEVEDO MOSQUEDA, R. CARREÑO AGUILERA, et al. "COMPUTATIONAL INTELLIGENCE FOR SHOEPRINT RECOGNITION." Fractals 27, no. 04 (2019): 1950080. http://dx.doi.org/10.1142/s0218348x19500804.

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Shoeprint marks present valuable information for forensic investigators to resolve a crime. These marks can be helpful to find the brand of the shoe and can make the investigation easier. In this paper, we present an associative model-based algorithm to match noisy shoeprint patterns with a brand of shoe. The shoeprints are corrupted with additive, subtractive and mixed noises. A particular case of subtractive noise are partial shoeprints such as toe, heel, left-half and right-half prints. The Morphological Associative Memories (MAMs) were applied. Both memories, max and min, recognize noisy s

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20

Jiang, Tinglei, Xiong Guo, Aiqing Lin, et al. "Bats increase vocal amplitude and decrease vocal complexity to mitigate noise interference during social communication." Animal Cognition 22, no. 2 (2019): 199–212. https://doi.org/10.5281/zenodo.13454176.

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(Uploaded by Plazi for the Bat Literature Project) Natural background noises are common in the acoustic environments in which most organisms have evolved. Therefore, the vocalization and sound perception systems of vocal animals are inherently equipped to overcome natural background noise. Human-generated noises, however, pose new challenges that can hamper audiovocal communication. The mechanisms animals use to cope with anthropogenic noise disturbances have been extensively explored in a variety of taxa. Bats emit echolocation pulses primarily to orient, locate and navigate, while social cal

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Jiang, Tinglei, Xiong Guo, Aiqing Lin, et al. "Bats increase vocal amplitude and decrease vocal complexity to mitigate noise interference during social communication." Animal Cognition 22, no. 2 (2019): 199–212. https://doi.org/10.5281/zenodo.13454176.

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(Uploaded by Plazi for the Bat Literature Project) Natural background noises are common in the acoustic environments in which most organisms have evolved. Therefore, the vocalization and sound perception systems of vocal animals are inherently equipped to overcome natural background noise. Human-generated noises, however, pose new challenges that can hamper audiovocal communication. The mechanisms animals use to cope with anthropogenic noise disturbances have been extensively explored in a variety of taxa. Bats emit echolocation pulses primarily to orient, locate and navigate, while social cal

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Jiang, Tinglei, Xiong Guo, Aiqing Lin, et al. "Bats increase vocal amplitude and decrease vocal complexity to mitigate noise interference during social communication." Animal Cognition 22, no. 2 (2019): 199–212. https://doi.org/10.5281/zenodo.13454176.

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(Uploaded by Plazi for the Bat Literature Project) Natural background noises are common in the acoustic environments in which most organisms have evolved. Therefore, the vocalization and sound perception systems of vocal animals are inherently equipped to overcome natural background noise. Human-generated noises, however, pose new challenges that can hamper audiovocal communication. The mechanisms animals use to cope with anthropogenic noise disturbances have been extensively explored in a variety of taxa. Bats emit echolocation pulses primarily to orient, locate and navigate, while social cal

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23

Jiang, Tinglei, Xiong Guo, Aiqing Lin, et al. "Bats increase vocal amplitude and decrease vocal complexity to mitigate noise interference during social communication." Animal Cognition 22, no. 2 (2019): 199–212. https://doi.org/10.5281/zenodo.13454176.

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(Uploaded by Plazi for the Bat Literature Project) Natural background noises are common in the acoustic environments in which most organisms have evolved. Therefore, the vocalization and sound perception systems of vocal animals are inherently equipped to overcome natural background noise. Human-generated noises, however, pose new challenges that can hamper audiovocal communication. The mechanisms animals use to cope with anthropogenic noise disturbances have been extensively explored in a variety of taxa. Bats emit echolocation pulses primarily to orient, locate and navigate, while social cal

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24

Jiang, Tinglei, Xiong Guo, Aiqing Lin, et al. "Bats increase vocal amplitude and decrease vocal complexity to mitigate noise interference during social communication." Animal Cognition 22, no. 2 (2019): 199–212. https://doi.org/10.5281/zenodo.13454176.

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(Uploaded by Plazi for the Bat Literature Project) Natural background noises are common in the acoustic environments in which most organisms have evolved. Therefore, the vocalization and sound perception systems of vocal animals are inherently equipped to overcome natural background noise. Human-generated noises, however, pose new challenges that can hamper audiovocal communication. The mechanisms animals use to cope with anthropogenic noise disturbances have been extensively explored in a variety of taxa. Bats emit echolocation pulses primarily to orient, locate and navigate, while social cal

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Anam, Choirul, Ariij Naufal, Kosuke Matsubara, Tosgioh Fujibuchi, and Geoff Dougherty. "A method for quantification of noise non-uniformity in computed tomography images: A computational study." Journal of Physics and Its Applications 5, no. 2 (2023): 48–57. http://dx.doi.org/10.14710/jpa.v5i2.17615.

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In computed tomography (CT), the noise is sometimes non-uniform, i.e. the noise magnitude may vary with the gradient level within the image. The purpose of this study was to quantify the noise non-uniformity in CT images using appropriate 1D and 2D computational phantoms, and to validate the effectiveness of the proposed concept in images filtered by the bilateral filter (BF), as an example of a non-linear filter. We first developed 1D and 2D computational phantoms, and Gaussian noises with several noise levels were then added to the phantoms. In addition, to simulate the real form of noise fr

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

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

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Zhong, Dongzhou, Wanan Deng, Peng Hou, et al. "Recognition of Noisy Digital Images Using the Asymmetric Coupling Semiconductor Chaotic Lasers Network." Photonics 10, no. 11 (2023): 1191. http://dx.doi.org/10.3390/photonics10111191.

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In this work, we construct a model of an asymmetrically coupled network of semiconductor chaotic lasers in order to recognize noisy digital images of digits 0–9, derived from different samples in the digital image sets 0–9 found within the MNIST dataset. Here, the lasers network consists of eight asymmetrically coupled semiconductor lasers. The chaotic lasers network is driven by the external inputs, which encode one noise digital image to be recognized. The outputs of the chaotic lasers network driven by a total of 40 samples from the digital image sets 0–9 are utilized as ten sets of referen

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Yang, Jie. "Combining Speech Enhancement and Cepstral Mean Normalization for LPC Cepstral Coefficients." Key Engineering Materials 474-476 (April 2011): 349–54. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.349.

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A mismatch between the training and testing in noisy circumstance often causes a drastic decrease in the performance of speech recognition system. The robust feature coefficients might suppress this sensitivity of mismatch during the recognition stage. In this paper, we investigate the noise robustness of LPC Cepstral Coefficients (LPCC) by using speech enhancement with feature post-processing. At front-end, speech enhancement in the wavelet domain is used to remove noise components from noisy signals. This enhanced processing adopts the combination of discrete wavelet transform (DWT), wavelet

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Weis, J., and J. Haaber. "Reducing Noise Through Awareness in the NICU." Developmental Observer 12, no. 1 (2019): 13. http://dx.doi.org/10.14434/do.v12i1.27843.

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In the NICU, environment sounds and noise can be challenging for the preterm and/or sick newborn baby. Reducing noise to provide an environment with appropriate and meaningful auditory experiences such as parents’ voices is important. Elimination of loud noises will furthermore beneﬁt the families and staﬀ. In 2016, the NICU at Rigshospitalet - Copenhagen University Hospital, collaborated with SoundEar™, a company that develops noise-meters for indicating and collecting noise levels, to develop a software program that was appropriate and easy to use. The aim was to support reduction in noise l

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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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Nisha, Bernad, and M. Victor Jose. "DTMF: Decision Based Trimmed Multimode Approach Filter for Denoising MRI Images." IT Journal Research and Development 7, no. 2 (2023): 152–72. http://dx.doi.org/10.25299/itjrd.2023.9463.

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The brain MRI image denoising is a challenging and attracting field for young researchers because it enhances the quality of medical images. Salt and pepper noise is the most dangerous noise which reduces the accuracy of brain diagnosis, and it damages the brain medical images severely, that leads to neurologists to fix incorrect treatments or surgery. The pitfalls raised in the existing denoising methods are less Peak signal to noise ratio, high time consumption and incapable for enormous level of noise range. Hence, this research proposes a novel denoising filter which is entitled as ‘Decisi

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Phung, Trung-Nghia, Huy-Khoi Do, Van-Tao Nguyen, and Quang-Vinh Thai. "Eigennoise Speech Recovery in Adverse Environments with Joint Compensation of Additive and Convolutive Noise." Advances in Acoustics and Vibration 2015 (November 3, 2015): 1–9. http://dx.doi.org/10.1155/2015/170183.

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The learning-based speech recovery approach using statistical spectral conversion has been used for some kind of distorted speech as alaryngeal speech and body-conducted speech (or bone-conducted speech). This approach attempts to recover clean speech (undistorted speech) from noisy speech (distorted speech) by converting the statistical models of noisy speech into that of clean speech without the prior knowledge on characteristics and distributions of noise source. Presently, this approach has still not attracted many researchers to apply in general noisy speech enhancement because of some ma

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Gao, Zhen Qiang, Zhi Guang Tian, and Yi Zhong Song. "Analyzing the Anti-Noise Performance of NAIRT Used in Deflection Tomography with Noised Projections." Applied Mechanics and Materials 373-375 (August 2013): 704–11. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.704.

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A new iteration reconstruction technique is suggested, which is named nonlinear auto-adjusting iterative reconstruction technique (NAIRT). Its anti-noise performance used in deflection tomography was tested with its projections added noises. A complicated air flow field, called model, was simulated, and was projected according to deflection tomographic algorithm. Thereupon, the real projections were obtained. A Series of random noises at different strength level were produced using randG function. Then, the noises were added to the real projections linearly. So, a series of noised projections

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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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Kang, Min Jeong. "The Meaning of Noise in The Wind in the Willows." British and American Language and Literature Association of Korea 148 (March 30, 2023): 1–21. http://dx.doi.org/10.21297/ballak.2023.148.1.

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The purpose of this study is to explore the meaning of noise in Kenneth Grahame’s The Wind in the Willows, a representative work of the Edwardian era. From the perspective of the social context, noise in this novel can be divided into two aspects: collision noise caused by class conflict and mechanical noise created by technological civilization. During the Edwardian period, the conflict between the upper class and the working class was deepening while the advent of automobiles was ushering in a new era of technological civilization. At times, the class conflicts would erupt into noisy public

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Yantén, Angélica V., Angel Cruz-Roa, and Francisco A. Sánchez. "Traffic noise affects foraging behavior and echolocation in the Lesser Bulldog Bat, Noctilio albiventris (Chiroptera: Noctilionidae)." Behavioural Processes 203 (June 12, 2022): 104775. https://doi.org/10.5281/zenodo.13427979.

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(Uploaded by Plazi for the Bat Literature Project) Urban noise, such as that of traffic, can affect the sensory capabilities in animals. Foragers acting optimally are expected to exploit feeding patches depending on the cost/benefit ratio, and some noises can cause increased foraging costs. We hypothesized that traffic noise affects foraging patch quality for aerial-insectivorous bats and predicted that there are measurable differences in their foraging activity and in their echolocation signals be tween nights with or without traffic noise. We tested these predictions in the Lesser Bulldog B

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Yantén, Angélica V., Angel Cruz-Roa, and Francisco A. Sánchez. "Traffic noise affects foraging behavior and echolocation in the Lesser Bulldog Bat, Noctilio albiventris (Chiroptera: Noctilionidae)." Behavioural Processes 203 (June 7, 2022): 104775. https://doi.org/10.5281/zenodo.13427979.

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Abstract:

(Uploaded by Plazi for the Bat Literature Project) Urban noise, such as that of traffic, can affect the sensory capabilities in animals. Foragers acting optimally are expected to exploit feeding patches depending on the cost/benefit ratio, and some noises can cause increased foraging costs. We hypothesized that traffic noise affects foraging patch quality for aerial-insectivorous bats and predicted that there are measurable differences in their foraging activity and in their echolocation signals be tween nights with or without traffic noise. We tested these predictions in the Lesser Bulldog B

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Yantén, Angélica V., Angel Cruz-Roa, and Francisco A. Sánchez. "Traffic noise affects foraging behavior and echolocation in the Lesser Bulldog Bat, Noctilio albiventris (Chiroptera: Noctilionidae)." Behavioural Processes 203 (July 3, 2022): 104775. https://doi.org/10.5281/zenodo.13427979.

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Abstract:

(Uploaded by Plazi for the Bat Literature Project) Urban noise, such as that of traffic, can affect the sensory capabilities in animals. Foragers acting optimally are expected to exploit feeding patches depending on the cost/benefit ratio, and some noises can cause increased foraging costs. We hypothesized that traffic noise affects foraging patch quality for aerial-insectivorous bats and predicted that there are measurable differences in their foraging activity and in their echolocation signals be tween nights with or without traffic noise. We tested these predictions in the Lesser Bulldog B

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39

Yantén, Angélica V., Angel Cruz-Roa, and Francisco A. Sánchez. "Traffic noise affects foraging behavior and echolocation in the Lesser Bulldog Bat, Noctilio albiventris (Chiroptera: Noctilionidae)." Behavioural Processes 203 (July 10, 2022): 104775. https://doi.org/10.5281/zenodo.13427979.

Full text

Abstract:

(Uploaded by Plazi for the Bat Literature Project) Urban noise, such as that of traffic, can affect the sensory capabilities in animals. Foragers acting optimally are expected to exploit feeding patches depending on the cost/benefit ratio, and some noises can cause increased foraging costs. We hypothesized that traffic noise affects foraging patch quality for aerial-insectivorous bats and predicted that there are measurable differences in their foraging activity and in their echolocation signals be tween nights with or without traffic noise. We tested these predictions in the Lesser Bulldog B

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Yantén, Angélica V., Angel Cruz-Roa, and Francisco A. Sánchez. "Traffic noise affects foraging behavior and echolocation in the Lesser Bulldog Bat, Noctilio albiventris (Chiroptera: Noctilionidae)." Behavioural Processes 203 (July 17, 2022): 104775. https://doi.org/10.5281/zenodo.13427979.

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Abstract:

(Uploaded by Plazi for the Bat Literature Project) Urban noise, such as that of traffic, can affect the sensory capabilities in animals. Foragers acting optimally are expected to exploit feeding patches depending on the cost/benefit ratio, and some noises can cause increased foraging costs. We hypothesized that traffic noise affects foraging patch quality for aerial-insectivorous bats and predicted that there are measurable differences in their foraging activity and in their echolocation signals be tween nights with or without traffic noise. We tested these predictions in the Lesser Bulldog B

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Yu, Boya, Yuying Chai, and Chao Wang. "Effect of the Exterior Traffic Noises on the Sound Environment Evaluation in Office Spaces with Different Interior Noise Conditions." Applied Sciences 14, no. 7 (2024): 3017. http://dx.doi.org/10.3390/app14073017.

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The present study focuses on the impact of exterior traffic noises on sound environment evaluation in office spaces, considering their interaction with interior noises. There were three interior noise conditions: silence, air-conditioner noise, and irrelevant speech noise. Six exterior traffic noises (road, maglev, tram, metro, conventional inter-city train, and high-speed train) were merged with interior noise clips to create the combined noise stimuli. Forty subjects participated in the experiment to assess the acoustic environment in office spaces exposed to multiple noises. The results sho

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Hegarty, Paul. "Noise threshold: Merzbow and the end of natural sound." Organised Sound 6, no. 3 (2001): 193–200. http://dx.doi.org/10.1017/s1355771801003053.

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When we ask what noise is, we would do well to remember that no single definition can function timelessly - this may well be the case with many terms, but one of the arguments of this essay is that noise is that which always fails to come into definition. Generally speaking, noise is taken to be a problem: unwanted sound, unorganised sound, excessively loud sound. Metaphorically, when we hear of noise being generated, we understand it to be something extraneous. Historically, though, noise has just as often signalled music, or pleasing sound, as its opposite. In the twentieth century, the noti

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Josephine, S., and S. Murugan. "Noise Removal from Brain MRI Images Using Adaptive Bayesian Shrinkage." Journal of Computational and Theoretical Nanoscience 17, no. 4 (2020): 1818–25. http://dx.doi.org/10.1166/jctn.2020.8446.

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In MR machine, surface coils, especially phased-arrays are used extensively for acquiring MR images with high spatial resolution. The signal intensities on images acquired using these coils have a non-uniform map due to coil sensitivity profile. Although these smooth intensity variations have little impact on visual diagnosis, they become critical issues when quantitative information is needed from the images. Sometimes, medical images are captured by low signal to noise ratio (SNR). The low SNR makes it difficult to detect anatomical structures because tissue characterization fails on those i

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Guo, Hui, Jin-Ming Liu, Cheng-Jie Zhang, and C. H. Oh. "Quantum discord of a three-qubit W-class state in noisy environments." Quantum Information and Computation 12, no. 7&8 (2012): 677–92. http://dx.doi.org/10.26421/qic12.7-8-12.

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We study the dynamics of the pairwise quantum discord (QD), classical correlation (CC), and entanglement of formation (EOF) for the three-qubit W-class state |W>_{123}=\frac 12(|100>_{123}+|010>_{123}+\sqrt{2}|001>_{123}) under the influence of various Markovian noises by analytically solving the master equation in the Lindblad form. Through numerical analysis, we find that EOF decreases asymptotically to zero with time for the dephasing noise, but it undergoes sudden death for the bit-flip noise, the isotropic noise, as well as the dissipative and noisy environments. Moreover, QD

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Jiang, Gaoxia, Jia Zhang, Xuefei Bai, Wenjian Wang, and Deyu Meng. "Which Is More Effective in Label Noise Cleaning, Correction or Filtering?" Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 11 (2024): 12866–73. http://dx.doi.org/10.1609/aaai.v38i11.29183.

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Most noise cleaning methods adopt one of the correction and filtering modes to build robust models. However, their effectiveness, applicability, and hyper-parameter insensitivity have not been carefully studied. We compare the two cleaning modes via a rebuilt error bound in noisy environments. At the dataset level, Theorem 5 implies that correction is more effective than filtering when the cleaned datasets have close noise rates. At the sample level, Theorem 6 indicates that confident label noises (large noise probabilities) are more suitable to be corrected, and unconfident noises (medium noi

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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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Wang, Guodong, Qian Dong, Zhenkuan Pan, Ximei Zhao, Jinbao Yang, and Cunliang Liu. "Active Contour Model for Ultrasound Images with Rayleigh Distribution." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/295320.

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Ultrasound images are often corrupted by multiplicative noises with Rayleigh distribution. The noises are strong and often called speckle noise, so segmentation is a hard work with this kind of noises. In this paper, we incorporate multiplicative noise removing model into active contour model for ultrasound images segmentation. To model gray level behavior of ultrasound images, the classic Rayleigh probability distribution is considered. Our model can segment the noisy ultrasound images very well. Finally, a fast method called Split-Bregman method is used for the easy implementation of segment

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Balachandran, G., and Praveen Kumar Gupta. "FPGA – Based Electrocardiography Signal Analysis System using (FIR) Filter." International Journal of Advance Research and Innovation 8, no. 1 (2020): 44–48. http://dx.doi.org/10.51976/ijari.812008.

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The cardiovascular attack is a more dangerous than other diseases and it is measured by ECG (Electro cardiograph) signals which is like a noisy signal in real time, especially in the field of telemedicine environment. The noisy ECG signals have more motion artifacts, electrical interference, etc. An adaptive filtering approach based on Discrete Wavelet Transform and an artificial neural network is proposed to reduce the noise in ECG signal. The quality of de-noised signal is improved by SVM algorithm. This suggested approach can successfully take out a broad scope of noise and our method achie

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EL MELLALI, TARIK, and YOUSSEF OUKNINE. "WEAK CONVERGENCE FOR QUASILINEAR STOCHASTIC HEAT EQUATION DRIVEN BY A FRACTIONAL NOISE WITH HURST PARAMETER H ∈ (½, 1)." Stochastics and Dynamics 13, no. 03 (2013): 1250024. http://dx.doi.org/10.1142/s0219493712500244.

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In this paper, we consider a quasi-linear stochastic heat equation in one dimension on [0, 1], with Dirichlet boundary conditions driven by an additive fractional white noise. We formally replace the random perturbation by a family of noisy inputs depending on a parameter n ∈ ℕ which can approximate the fractional noise in some sense. Then, we provide sufficient conditions ensuring that the real-valued mild solution of the SPDE perturbed by this family of noises converges in law, in the space [Formula: see text] of continuous functions, to the solution of the fractional noise driven SPDE.

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C, Shankara, and A. Hariprasad S. "Noise Removal Techniques for Lung Cancer CT Images." Indian Journal of Science and Technology 15, no. 32 (2022): 1577–86. https://doi.org/10.17485/IJST/v15i32.798.

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Abstract <strong>Objectives:</strong> To analyze various filtering methods to eliminate noises present in the lung CT images and to enhance the image, which help in further evaluation of CT images for accurate lung cancer detection. To compare the proposed method with existing filtering techniques and to find the best filtering technique. <strong>Methods:</strong> For input lung CT images noises like salt along with pepper noise and speckle noise are added. For noisy images different filtering methods like Median filter, Wiener filter, Gaussian filter and Guided filter are appli

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