In this paper, an adaptive multiresolution speech enhancement algorithm based on wavelet transform is put forward. It can make adaptive filtering to noise speech both at scales and among scales. So that the noise part...In this paper, an adaptive multiresolution speech enhancement algorithm based on wavelet transform is put forward. It can make adaptive filtering to noise speech both at scales and among scales. So that the noise parts during the frequency intervals which decrease hearing quality mostly are reduced efficiently. Both the SNR and subject hearing quality of denoised speech are high and good.展开更多
The theory of detecling ridges in the modulus of the continuous wavelet transform is presented as well as reconstructing signal by using information on ridges,To periodic signal we suppose Morlet wavelet as basic wave...The theory of detecling ridges in the modulus of the continuous wavelet transform is presented as well as reconstructing signal by using information on ridges,To periodic signal we suppose Morlet wavelet as basic wavelet, and research the local extreme point and extrema of the wavelet transform on periodic function for the collection of signal＇ s instantaneous amplitude and period.展开更多
A mixed scheme based on Wavelet Transformation (WT) is proposed for image edge detection. The scheme combines the wavelet transform and traditional Sobel and LoG (Laplacian of Gaussian) operator edge-detection algorit...A mixed scheme based on Wavelet Transformation (WT) is proposed for image edge detection. The scheme combines the wavelet transform and traditional Sobel and LoG (Laplacian of Gaussian) operator edge-detection algorithms. The precise theory analysis is given to show that the wavelet transformation has an advantage for signal processing. Simulation results show that the new scheme is better than only using the Sobel or LoG methods. Complexity analysis is also given and the conclusion is acceptable, therefore the proposed scheme is effective for edge detection.展开更多
Mirnov signals mixed with interferences are a kind of non-stationary signal. It cannot obtain satisfactory effects to extract MHD signals from mirnov signals by Fourier Transform. This paper suggests that the wavelet ...Mirnov signals mixed with interferences are a kind of non-stationary signal. It cannot obtain satisfactory effects to extract MHD signals from mirnov signals by Fourier Transform. This paper suggests that the wavelet transform can be used to treat mirnov signals. Theoretical analysis and experimental result have indicated that using the time-frequency analysis characteristics of the wavelet transform to filter mirnov signals can remove effectively interferences and extract useful MHD signals.展开更多
This paper first reviews the application research works of wavelet transform on the fluid mechanics. Then the theories of continuous wavelet transform and multi-dimensional orthogonal(discrete) wavelet transform, incl...This paper first reviews the application research works of wavelet transform on the fluid mechanics. Then the theories of continuous wavelet transform and multi-dimensional orthogonal(discrete) wavelet transform, including wavelet multiresolution analysis, are introduced. At last the applications of wavelet transform on 2 D and 3 D turbulent wakes and turbulent boundary layer flows are described based on the hot-wire, 2 D particle image velocimetry(PIV) and 3 D tomographic PIV.展开更多
With the new system radar put into practical use, the characteristics of complex radar signals are changing and developing. The traditional analysis method of one-dimensional transformation domain is no longer applica...With the new system radar put into practical use, the characteristics of complex radar signals are changing and developing. The traditional analysis method of one-dimensional transformation domain is no longer applicable to the modern radar signal processing, and it is necessary to seek new methods in the two-dimensional transformation domain. The time-frequency analysis method is the most widely used method in the two-dimensional transformation domain. In this paper, two typical time-frequency analysis methods of short-time Fourier transform and Wigner-Ville distribution are studied by analyzing the time-frequency transform of typical radar reconnaissance linear frequency modulation signal, aiming at the problem of low accuracy and sen-sitivity to the signal noise of common methods, the improved wavelet transform algorithm was proposed.展开更多
In order to investigate the characteristics of sensorimotor cortex during motor execution(ME), voluntary, stimulated and imaginary finger flexions were performed by ten volunteer subjects. Electroencephalogram(EEG) da...In order to investigate the characteristics of sensorimotor cortex during motor execution(ME), voluntary, stimulated and imaginary finger flexions were performed by ten volunteer subjects. Electroencephalogram(EEG) data were recorded according to the modified 10-20 International EEG System. The patterns were compared by the analysis of the motion-evoked EEG signals focusing on the contralateral(C3) and ipsilateral(C4) channels for hemispheric differences. The EEG energy distributions at alpha(8—13 Hz), beta(14—30 Hz) and gamma(30—50 Hz) bands were computed by wavelet transform(WT) and compared by the analysis of variance(ANOVA). The timefrequency(TF) analysis indicated that there existed a contralateral dominance of alpha post-movement event-related synchronization(ERS) pattern during the voluntary task, and that the energy of alpha band increased in the ipsilateral area during the stimulated(median nerve of wrist) task. Besides, the contralateral alpha and beta event-related desynchronization(ERD) patterns were observed in both stimulated and imaginary tasks. Another significant difference was found in the mean power values of gamma band(p<0.01)between the imaginary and other tasks. The results show that significant hemispheric differences such as alpha and beta band EEG energy distributions and TF changing phenomena(ERS/ERD) were found between C3 and C4 areas during all of the three patterns. The largest energy distribution was always at the alpha band for each task.展开更多
When disturbed, the interaction between power grid and wind farm may cause serious sub/super-synchronous oscillation (SSO), affecting the security and stability of the system. It is therefore important to detect the t...When disturbed, the interaction between power grid and wind farm may cause serious sub/super-synchronous oscillation (SSO), affecting the security and stability of the system. It is therefore important to detect the time-varying amplitude and frequency of SSO to provide information for its control. The matching synchroextracting wavelet transform (MSEWT) is a new method proposed in this paper to serve this purpose. Based on the original synchrosqueezing wavelet transform, MSEWT uses a synchronous extraction operator to calculate the time-frequency coefficients and a chirp-rate estimation to modify the instantaneous frequency estimation. Thus, MSEWT can improve the concentration degree and reconstruction accuracy of the signal's time-frequency representation without iterative calculation, and can achieve superior noise robustness. After the time-frequency analysis and modal decomposition of the SSO by MSEWT, the amplitudes and frequencies of each oscillation component can be obtained by Hilbert transform (HT). The simulation studies demonstrate that the proposed scheme can accurately identify the modal parameters of SSO even in the case of noise interference, providing a reliable reference for stable operation of power system time-frequency.展开更多
This paper studies Synthetic Aperture Radar (SAR) images contaminated by the coherent speckle noise with the multiresolution analysis of wavelet transform. This study shows that the influences of the speckle on differ...This paper studies Synthetic Aperture Radar (SAR) images contaminated by the coherent speckle noise with the multiresolution analysis of wavelet transform. This study shows that the influences of the speckle on different frequency components of the SAR image are different, and that the SAR image and the speckle have different manners of singularity. So, this paper presents a denoising method of wavelet analysis to reduce the speckle. Some experiments approve that this method not only suppresses the speckle effectively, but also preserves as much target characteristics of the original image as possible. It shows that this denoising method of wavelet analysis offers a very attractive alternative to suppress the coherent speckle noise of the SAR image.展开更多
Sound waves propagate well underwater making it useful for target locating and communication.Underwater acoustic noise(UWAN)affects the reliability in applications where the noise comes from multiple sources.In this p...Sound waves propagate well underwater making it useful for target locating and communication.Underwater acoustic noise(UWAN)affects the reliability in applications where the noise comes from multiple sources.In this paper,a novel signal de-noising technique is proposed using S-transform.From the time-frequency representation,de-noising is performed using soft thresholding with universal threshold estimation which is then reconstructed.The UWAN used for the validation is sea truth data collected at Desaru beach on the eastern shore of Johor in Malaysia with the use of broadband hydrophones.The comparison is made with the more conventionally used wavelet transform de-noising method.Two types of signals are evaluated:fixed frequency signals and time-varying signals.The results demonstrate that the proposed method shows better signal to noise ratio(SNR)by 4 dB and lower root mean square error(RMSE)by 3 dB achieved at the Nyquist sampling frequency compared to the previously proposed de-noising method like wavelet transform.展开更多
Multiresolutional signal processing has been employed in image processing and computer vision to achieve improved performance that cannot be achieved using conventional signal processing techniques at only one resolut...Multiresolutional signal processing has been employed in image processing and computer vision to achieve improved performance that cannot be achieved using conventional signal processing techniques at only one resolution level [1,2,5,6] . In this paper,we have associated the thought of multiresolutional analysis with traditional Kalman filtering and proposed A new fusion algorithm based on singular Sensor and Multipale Models for maneuvering target tracking.展开更多
Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals with steady and transitory properti...Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals with steady and transitory properties, it has limits. The Wavelet Packet Decomposition (WPD) is a novel technique that we suggest in this study as a way to improve the Fourier Transform and get beyond these drawbacks. In this experiment, we specifically considered the utilization of Daubechies level 4 for the wavelet transformation. The choice of Daubechies level 4 was motivated by several reasons. Daubechies wavelets are known for their compact support, orthogonality, and good time-frequency localization. By choosing Daubechies level 4, we aimed to strike a balance between preserving important transient information and avoiding excessive noise or oversmoothing in the transformed signal. Then we compared the outcomes of our suggested approach to the conventional Fourier Transform using a non-stationary signal. The findings demonstrated that the suggested method offered a more accurate representation of non-stationary and transient signals in the frequency domain. Our method precisely showed a 12% reduction in MSE and a 3% rise in PSNR for the standard Fourier transform, as well as a 35% decrease in MSE and an 8% increase in PSNR for voice signals when compared to the traditional wavelet packet decomposition method.展开更多
This paper extends the definition of fractional Fourier transform （FRFT） proposed by Namias V by using other orthonormal bases for L^2（R） instead of Hermite-Gaussian functions. The new orthonormal basis is gained ...This paper extends the definition of fractional Fourier transform （FRFT） proposed by Namias V by using other orthonormal bases for L^2（R） instead of Hermite-Gaussian functions. The new orthonormal basis is gained indirectly from multiresolution analysis and orthonormal wavelets. The so defined FRFT is called wavelets-fractional Fourier transform.展开更多
In this paper, we construct a kind of bivariate real-valued orthogonal periodic wavelets. The corre-sponding decomposition and reconstruction algorithms involve only 8 terms respectively which are very simple in pract...In this paper, we construct a kind of bivariate real-valued orthogonal periodic wavelets. The corre-sponding decomposition and reconstruction algorithms involve only 8 terms respectively which are very simple in practical computation. Moreover, the relation between periodic wavelets and Fourier series is also discussed.展开更多
In this paper, the notion of p-wavelet packets on the positive half-line P＋ is introduced. A new method for constructing non-orthogonal wavelet packets related to Walsh functions is developed by splitting the wavelet...In this paper, the notion of p-wavelet packets on the positive half-line P＋ is introduced. A new method for constructing non-orthogonal wavelet packets related to Walsh functions is developed by splitting the wavelet subspaces directly instead of using the lowpass and high-pass filters associated with the multiresolution analysis as used in the classical theory of wavelet packets. Further, the method overcomes the difficulty of constructing non-orthogonal wavelet packets of the dilation factor p 〉 2.展开更多
文摘In this paper, an adaptive multiresolution speech enhancement algorithm based on wavelet transform is put forward. It can make adaptive filtering to noise speech both at scales and among scales. So that the noise parts during the frequency intervals which decrease hearing quality mostly are reduced efficiently. Both the SNR and subject hearing quality of denoised speech are high and good.
基金Supported by the National Natural Science Founda-tion of China (49771060)
文摘The theory of detecling ridges in the modulus of the continuous wavelet transform is presented as well as reconstructing signal by using information on ridges,To periodic signal we suppose Morlet wavelet as basic wavelet, and research the local extreme point and extrema of the wavelet transform on periodic function for the collection of signal＇ s instantaneous amplitude and period.
基金Supported by the National Defence 973 project(2002HS0604,2002HS0634)
文摘A mixed scheme based on Wavelet Transformation (WT) is proposed for image edge detection. The scheme combines the wavelet transform and traditional Sobel and LoG (Laplacian of Gaussian) operator edge-detection algorithms. The precise theory analysis is given to show that the wavelet transformation has an advantage for signal processing. Simulation results show that the new scheme is better than only using the Sobel or LoG methods. Complexity analysis is also given and the conclusion is acceptable, therefore the proposed scheme is effective for edge detection.
基金This work was supported by the National Nature Science Foundation of China No.19889504.
文摘Mirnov signals mixed with interferences are a kind of non-stationary signal. It cannot obtain satisfactory effects to extract MHD signals from mirnov signals by Fourier Transform. This paper suggests that the wavelet transform can be used to treat mirnov signals. Theoretical analysis and experimental result have indicated that using the time-frequency analysis characteristics of the wavelet transform to filter mirnov signals can remove effectively interferences and extract useful MHD signals.
基金the National Natural Science Foundation of China(Nos.11721202 and 11772035)support from JSPS Research Fellowships for Young Scientists(2019~2022)。
文摘This paper first reviews the application research works of wavelet transform on the fluid mechanics. Then the theories of continuous wavelet transform and multi-dimensional orthogonal(discrete) wavelet transform, including wavelet multiresolution analysis, are introduced. At last the applications of wavelet transform on 2 D and 3 D turbulent wakes and turbulent boundary layer flows are described based on the hot-wire, 2 D particle image velocimetry(PIV) and 3 D tomographic PIV.
文摘With the new system radar put into practical use, the characteristics of complex radar signals are changing and developing. The traditional analysis method of one-dimensional transformation domain is no longer applicable to the modern radar signal processing, and it is necessary to seek new methods in the two-dimensional transformation domain. The time-frequency analysis method is the most widely used method in the two-dimensional transformation domain. In this paper, two typical time-frequency analysis methods of short-time Fourier transform and Wigner-Ville distribution are studied by analyzing the time-frequency transform of typical radar reconnaissance linear frequency modulation signal, aiming at the problem of low accuracy and sen-sitivity to the signal noise of common methods, the improved wavelet transform algorithm was proposed.
基金Supported by the National Natural Science Foundation of China(No.81222021,No.61172008,No.81171423)National Key Technology Research and Development Program of the Ministry of Science and Technology of China(No.2012BAI34B02)Program for New Century Excellent Talents in University of the Ministry of Education of China(No.NCET-10-0618)
文摘In order to investigate the characteristics of sensorimotor cortex during motor execution(ME), voluntary, stimulated and imaginary finger flexions were performed by ten volunteer subjects. Electroencephalogram(EEG) data were recorded according to the modified 10-20 International EEG System. The patterns were compared by the analysis of the motion-evoked EEG signals focusing on the contralateral(C3) and ipsilateral(C4) channels for hemispheric differences. The EEG energy distributions at alpha(8—13 Hz), beta(14—30 Hz) and gamma(30—50 Hz) bands were computed by wavelet transform(WT) and compared by the analysis of variance(ANOVA). The timefrequency(TF) analysis indicated that there existed a contralateral dominance of alpha post-movement event-related synchronization(ERS) pattern during the voluntary task, and that the energy of alpha band increased in the ipsilateral area during the stimulated(median nerve of wrist) task. Besides, the contralateral alpha and beta event-related desynchronization(ERD) patterns were observed in both stimulated and imaginary tasks. Another significant difference was found in the mean power values of gamma band(p<0.01)between the imaginary and other tasks. The results show that significant hemispheric differences such as alpha and beta band EEG energy distributions and TF changing phenomena(ERS/ERD) were found between C3 and C4 areas during all of the three patterns. The largest energy distribution was always at the alpha band for each task.
基金supported by National Natural Science Foundation of China(No.52077081)Guangdong Basic and Applied Basic Research Foundation(No.2022A1515011608).
文摘When disturbed, the interaction between power grid and wind farm may cause serious sub/super-synchronous oscillation (SSO), affecting the security and stability of the system. It is therefore important to detect the time-varying amplitude and frequency of SSO to provide information for its control. The matching synchroextracting wavelet transform (MSEWT) is a new method proposed in this paper to serve this purpose. Based on the original synchrosqueezing wavelet transform, MSEWT uses a synchronous extraction operator to calculate the time-frequency coefficients and a chirp-rate estimation to modify the instantaneous frequency estimation. Thus, MSEWT can improve the concentration degree and reconstruction accuracy of the signal's time-frequency representation without iterative calculation, and can achieve superior noise robustness. After the time-frequency analysis and modal decomposition of the SSO by MSEWT, the amplitudes and frequencies of each oscillation component can be obtained by Hilbert transform (HT). The simulation studies demonstrate that the proposed scheme can accurately identify the modal parameters of SSO even in the case of noise interference, providing a reliable reference for stable operation of power system time-frequency.
基金Supported by both Chinese National Natural FoundationNational 863 Hi-Tech Project Foundation
文摘This paper studies Synthetic Aperture Radar (SAR) images contaminated by the coherent speckle noise with the multiresolution analysis of wavelet transform. This study shows that the influences of the speckle on different frequency components of the SAR image are different, and that the SAR image and the speckle have different manners of singularity. So, this paper presents a denoising method of wavelet analysis to reduce the speckle. Some experiments approve that this method not only suppresses the speckle effectively, but also preserves as much target characteristics of the original image as possible. It shows that this denoising method of wavelet analysis offers a very attractive alternative to suppress the coherent speckle noise of the SAR image.
基金The authors would like to thank the Universiti Teknologi Malaysia(UTM)and Ministry of Higher Education(MOHE)Malaysia for supporting this work.
文摘Sound waves propagate well underwater making it useful for target locating and communication.Underwater acoustic noise(UWAN)affects the reliability in applications where the noise comes from multiple sources.In this paper,a novel signal de-noising technique is proposed using S-transform.From the time-frequency representation,de-noising is performed using soft thresholding with universal threshold estimation which is then reconstructed.The UWAN used for the validation is sea truth data collected at Desaru beach on the eastern shore of Johor in Malaysia with the use of broadband hydrophones.The comparison is made with the more conventionally used wavelet transform de-noising method.Two types of signals are evaluated:fixed frequency signals and time-varying signals.The results demonstrate that the proposed method shows better signal to noise ratio(SNR)by 4 dB and lower root mean square error(RMSE)by 3 dB achieved at the Nyquist sampling frequency compared to the previously proposed de-noising method like wavelet transform.
文摘Multiresolutional signal processing has been employed in image processing and computer vision to achieve improved performance that cannot be achieved using conventional signal processing techniques at only one resolution level [1,2,5,6] . In this paper,we have associated the thought of multiresolutional analysis with traditional Kalman filtering and proposed A new fusion algorithm based on singular Sensor and Multipale Models for maneuvering target tracking.
文摘Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals with steady and transitory properties, it has limits. The Wavelet Packet Decomposition (WPD) is a novel technique that we suggest in this study as a way to improve the Fourier Transform and get beyond these drawbacks. In this experiment, we specifically considered the utilization of Daubechies level 4 for the wavelet transformation. The choice of Daubechies level 4 was motivated by several reasons. Daubechies wavelets are known for their compact support, orthogonality, and good time-frequency localization. By choosing Daubechies level 4, we aimed to strike a balance between preserving important transient information and avoiding excessive noise or oversmoothing in the transformed signal. Then we compared the outcomes of our suggested approach to the conventional Fourier Transform using a non-stationary signal. The findings demonstrated that the suggested method offered a more accurate representation of non-stationary and transient signals in the frequency domain. Our method precisely showed a 12% reduction in MSE and a 3% rise in PSNR for the standard Fourier transform, as well as a 35% decrease in MSE and an 8% increase in PSNR for voice signals when compared to the traditional wavelet packet decomposition method.
基金Project supported by the Young People Foundation of Zhejiang Normal University, China (Grant No KYJ06Y07150)
文摘This paper extends the definition of fractional Fourier transform （FRFT） proposed by Namias V by using other orthonormal bases for L^2（R） instead of Hermite-Gaussian functions. The new orthonormal basis is gained indirectly from multiresolution analysis and orthonormal wavelets. The so defined FRFT is called wavelets-fractional Fourier transform.
文摘In this paper, we construct a kind of bivariate real-valued orthogonal periodic wavelets. The corre-sponding decomposition and reconstruction algorithms involve only 8 terms respectively which are very simple in practical computation. Moreover, the relation between periodic wavelets and Fourier series is also discussed.
文摘In this paper, the notion of p-wavelet packets on the positive half-line P＋ is introduced. A new method for constructing non-orthogonal wavelet packets related to Walsh functions is developed by splitting the wavelet subspaces directly instead of using the lowpass and high-pass filters associated with the multiresolution analysis as used in the classical theory of wavelet packets. Further, the method overcomes the difficulty of constructing non-orthogonal wavelet packets of the dilation factor p 〉 2.
