Label-free nanopore sensors have emerged as a new generation technology of DNA sequencing and have been widely used for single molecule analysis.Since the firstα-hemolysin biological nanopore,various types of nanopor...Label-free nanopore sensors have emerged as a new generation technology of DNA sequencing and have been widely used for single molecule analysis.Since the firstα-hemolysin biological nanopore,various types of nanopores made of different materials have been under extensive development.Noise represents a common challenge among all types of nanopore sensors.The nanopore noise can be decomposed into four components in the frequency domain(1/f noise,white noise,dielectric noise,and amplifier noise).In this work,we reviewed and summarized the physicalmodels,origins,and reduction methods for each of these noise components.For the first time,we quantitatively benchmarked the root mean square(RMS)noise levels for different types of nanopores,demonstrating a clear material-dependent RMS noise.We anticipate this review article will enhance the understanding of nanopore sensor noises and provide an informative tutorial for developing future nanopore sensors with a high signal-to-noise ratio.展开更多
In order to reduce noise effectively in the welding defect image and preserve the minutiae information, a noise reduction method of welding defect image based on nonsubsampled contourlet transform(NSCT) and anisotropi...In order to reduce noise effectively in the welding defect image and preserve the minutiae information, a noise reduction method of welding defect image based on nonsubsampled contourlet transform(NSCT) and anisotropic diffusion is proposed. Firstly, an X-ray welding defect image is decomposed by NSCT. Then total variation(TV) model and Catte_PM model are used for the obtained low-pass component and band-pass components, respectively. Finally, the denoised image is synthesized by inverse NSCT. Experimental results show that, compared with the hybrid method of wavelet threshold shrinkage with TV diffusion, the method combining NSCT with P_Laplace diffusion, and the method combining contourlet with TV model and adaptive contrast diffusion, the proposed method has a great improvement in the aspects of subjective visual effect, peak signal-to-noise ratio(PSNR) and mean-square error(MSE). Noise is suppressed more effectively and the minutiae information is preserved better in the image.展开更多
This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the ps...This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.展开更多
This paper describes a method for reducing sudden noise using noise detection and classification methods, and noise power estimation. Sudden noise detection and classification have been dealt with in our previous stud...This paper describes a method for reducing sudden noise using noise detection and classification methods, and noise power estimation. Sudden noise detection and classification have been dealt with in our previous study. In this paper, GMM-based noise reduction is performed using the detection and classification results. As a result of classification, we can determine the kind of noise we are dealing with, but the power is unknown. In this paper, this problem is solved by combining an estimation of noise power with the noise reduction method. In our experiments, the proposed method achieved good performance for recognition of utterances overlapped by sudden noises.展开更多
In order to predict the levels of corona noise from high-voltage alternating current (AC) transmission lines,the mechanism of corona noise and the corresponding theoretical prediction model are investigated. On the ba...In order to predict the levels of corona noise from high-voltage alternating current (AC) transmission lines,the mechanism of corona noise and the corresponding theoretical prediction model are investigated. On the basis of Drude model,the motion of positive and negative ions produced by high-voltage corona is analyzed,and the mechanism of corona noise is discovered. The theoretical prediction model is put forward by using Kirchhoff formula,which is verified by the well agreement between our result and others',considering the case of three-phase single lines. Moreover,the calculation results show that for both single and bundled lines,the sound pressure level of the typical frequency,i.e. twice the power frequency,attenuates slowly and leads to an obviously interferential phenomenon near the transmission lines,but the level of the bundled lines is smaller than that of the single ones under the same transmission voltage. Based on the mechanism of corona noise and the prediction model,it is obvious that bundled lines and/or increased line radius can be adopted to reduce corona noise in the practical engineering applications effectively. This model can also provide a theoretical guidance for the high-voltage AC transmission line design.展开更多
The paper not only studies the noise reduction methods of chaotic time series with noise and its reconstruction techniques, but also discusses prediction techniques of chaotic time series and its applications based on...The paper not only studies the noise reduction methods of chaotic time series with noise and its reconstruction techniques, but also discusses prediction techniques of chaotic time series and its applications based on chaotic data noise reduction. In the paper, we first decompose the phase space of chaotic time series to range space and null noise space. Secondly we restructure original chaotic time series in range space. Lastly on the basis of the above, we establish order of the nonlinear model and make use of the nonlinear model to predict some research. The result indicates that the nonlinear model has very strong ability of approximation function, and Chaos predict method has certain tutorial significance to the practical problems.展开更多
以NACA 65(12)–10独立基准叶片为对象,使用线性传声器阵列和SODIX(SOurce DIrectivity modeling in the cross-spectral matriX)方法对基准叶片前缘噪声指向性分布特征及波浪前缘对叶片前缘噪声的影响进行了实验研究。开发了SODIX数据...以NACA 65(12)–10独立基准叶片为对象,使用线性传声器阵列和SODIX(SOurce DIrectivity modeling in the cross-spectral matriX)方法对基准叶片前缘噪声指向性分布特征及波浪前缘对叶片前缘噪声的影响进行了实验研究。开发了SODIX数据处理程序并进行了数值仿真验证,结果表明:不同指向角下计算结果的最大误差不超过0.26 dB。在半消声室内,利用由31个传声器组成的非均匀分布优化阵列,对NACA 65(12)–10独立基准叶片和仿生学叶片的前缘噪声开展了参数化声学实验。结果表明:在40°~142°指向角测量范围内,基准叶片前缘噪声指向性符合典型偶极子声源特征,峰值在130°指向角附近;随着频率升高,基准叶片前缘噪声指向性产生了显著的“波瓣”现象,频率越高,“波瓣”越多。进一步研究表明:不同波长和幅值的前缘构型都可以有效降低指向角测量范围内的前缘噪声;与波浪前缘的波长相比,波浪前缘的幅值对前缘噪声的影响更为显著,特别是在90°~120°指向角范围内,A30W20叶型的降噪量可达7.71 dB。展开更多
In order to discuss the finite-size effect and the anomalous dynamic scaling behaviour of Das Sarma-Tamborenea growth model, the （1＋1）-dimensional Das Sarma-Tamborenea model is simulated on a large length scale by ...In order to discuss the finite-size effect and the anomalous dynamic scaling behaviour of Das Sarma-Tamborenea growth model, the （1＋1）-dimensional Das Sarma-Tamborenea model is simulated on a large length scale by using the kinetic Monte-Carlo method. In the simulation, noise reduction technique is used in order to eliminate the crossover effect. Our results show that due to the existence of the finite-size effect, the effective global roughness exponent of the （1＋1）-dimensional Das Sarma-Tamborenea model systematically decreases with system size L increasing when L 〉 256. This finding proves the conjecture by Aarao Reis[Aarao Reis F D A 2004 Phys. Rev. E 70 031607]. In addition, our simulation results also show that the Das Sarma-Tamborenea model in 1＋1 dimensions indeed exhibits intrinsic anomalous scaling behaviour.展开更多
基金the National Science Foundation under Grant No.1710831,1902503,and 1912410.Any opinions,findingsconclusions or recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the National Science Foundation+2 种基金This project was also partially supported by National Key Research and Development Program of China(2016YFB0402700)National Key Scientific Instrument and Equipment Development Projects of China(51727901)China Postdoctoral Science Foundation(2017M620942).
文摘Label-free nanopore sensors have emerged as a new generation technology of DNA sequencing and have been widely used for single molecule analysis.Since the firstα-hemolysin biological nanopore,various types of nanopores made of different materials have been under extensive development.Noise represents a common challenge among all types of nanopore sensors.The nanopore noise can be decomposed into four components in the frequency domain(1/f noise,white noise,dielectric noise,and amplifier noise).In this work,we reviewed and summarized the physicalmodels,origins,and reduction methods for each of these noise components.For the first time,we quantitatively benchmarked the root mean square(RMS)noise levels for different types of nanopores,demonstrating a clear material-dependent RMS noise.We anticipate this review article will enhance the understanding of nanopore sensor noises and provide an informative tutorial for developing future nanopore sensors with a high signal-to-noise ratio.
基金Supported by the National Natural Science Foundation of China(No.60872065)Open Foundation of State Key Laboratory of Advanced Welding and Connection,Harbin Institute of Technology(AWPT-M04)Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘In order to reduce noise effectively in the welding defect image and preserve the minutiae information, a noise reduction method of welding defect image based on nonsubsampled contourlet transform(NSCT) and anisotropic diffusion is proposed. Firstly, an X-ray welding defect image is decomposed by NSCT. Then total variation(TV) model and Catte_PM model are used for the obtained low-pass component and band-pass components, respectively. Finally, the denoised image is synthesized by inverse NSCT. Experimental results show that, compared with the hybrid method of wavelet threshold shrinkage with TV diffusion, the method combining NSCT with P_Laplace diffusion, and the method combining contourlet with TV model and adaptive contrast diffusion, the proposed method has a great improvement in the aspects of subjective visual effect, peak signal-to-noise ratio(PSNR) and mean-square error(MSE). Noise is suppressed more effectively and the minutiae information is preserved better in the image.
基金partially supported by the National Natural Science Foundation of China (Nos.11590772, 11590770)the Pre-research Project for Equipment of General Information System (No.JZX2017-0994/Y306)
文摘This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.
文摘This paper describes a method for reducing sudden noise using noise detection and classification methods, and noise power estimation. Sudden noise detection and classification have been dealt with in our previous study. In this paper, GMM-based noise reduction is performed using the detection and classification results. As a result of classification, we can determine the kind of noise we are dealing with, but the power is unknown. In this paper, this problem is solved by combining an estimation of noise power with the noise reduction method. In our experiments, the proposed method achieved good performance for recognition of utterances overlapped by sudden noises.
文摘In order to predict the levels of corona noise from high-voltage alternating current (AC) transmission lines,the mechanism of corona noise and the corresponding theoretical prediction model are investigated. On the basis of Drude model,the motion of positive and negative ions produced by high-voltage corona is analyzed,and the mechanism of corona noise is discovered. The theoretical prediction model is put forward by using Kirchhoff formula,which is verified by the well agreement between our result and others',considering the case of three-phase single lines. Moreover,the calculation results show that for both single and bundled lines,the sound pressure level of the typical frequency,i.e. twice the power frequency,attenuates slowly and leads to an obviously interferential phenomenon near the transmission lines,but the level of the bundled lines is smaller than that of the single ones under the same transmission voltage. Based on the mechanism of corona noise and the prediction model,it is obvious that bundled lines and/or increased line radius can be adopted to reduce corona noise in the practical engineering applications effectively. This model can also provide a theoretical guidance for the high-voltage AC transmission line design.
基金Project supported by the National Natural Science Foundation of China(Nos.70271071,19990510,D0200201)
文摘The paper not only studies the noise reduction methods of chaotic time series with noise and its reconstruction techniques, but also discusses prediction techniques of chaotic time series and its applications based on chaotic data noise reduction. In the paper, we first decompose the phase space of chaotic time series to range space and null noise space. Secondly we restructure original chaotic time series in range space. Lastly on the basis of the above, we establish order of the nonlinear model and make use of the nonlinear model to predict some research. The result indicates that the nonlinear model has very strong ability of approximation function, and Chaos predict method has certain tutorial significance to the practical problems.
基金supported by the National Natural Science Foundation of China (Grant No. 10674177)the Youth Foundation of China University of Mining & Technology (Grant No. 2008A035)
文摘In order to discuss the finite-size effect and the anomalous dynamic scaling behaviour of Das Sarma-Tamborenea growth model, the （1＋1）-dimensional Das Sarma-Tamborenea model is simulated on a large length scale by using the kinetic Monte-Carlo method. In the simulation, noise reduction technique is used in order to eliminate the crossover effect. Our results show that due to the existence of the finite-size effect, the effective global roughness exponent of the （1＋1）-dimensional Das Sarma-Tamborenea model systematically decreases with system size L increasing when L 〉 256. This finding proves the conjecture by Aarao Reis[Aarao Reis F D A 2004 Phys. Rev. E 70 031607]. In addition, our simulation results also show that the Das Sarma-Tamborenea model in 1＋1 dimensions indeed exhibits intrinsic anomalous scaling behaviour.
