A three-dimensional analysis of a simply-supported functionally graded rectangular plate with an arbitrary distribution of material properties is made using a simple and effective method based on the Haar wavelet. Wit...A three-dimensional analysis of a simply-supported functionally graded rectangular plate with an arbitrary distribution of material properties is made using a simple and effective method based on the Haar wavelet. With good features in treating singularities, Haar series solution converges rapidly for arbitrary distributions, especially for the case where the material properties change rapidly in some regions. Through numerical examples the influences of the ratio of material constants on the top and bottom surfaces and different material gradient distributions on the structural response of the plate to mechanical stimuli are studied.展开更多
Surface electromyogram （EMG） signals were identified by fractal dimension.Two patterns of surface EMG signals were acquired from 30 healthy volunteers＇ right forearm flexor respectively in the process of forearm su...Surface electromyogram （EMG） signals were identified by fractal dimension.Two patterns of surface EMG signals were acquired from 30 healthy volunteers＇ right forearm flexor respectively in the process of forearm supination （FS） and forearm pronation （FP）.After the raw action surface EMG （ASEMG） signal was decomposed into several sub-signals with wavelet packet transform （WPT）,five fractal dimensions were respectively calculated from the raw signal and four sub-signals by the method based on fuzzy self-similarity.The results show that calculated from the sub-signal in the band 0 to 125 Hz,the fractal dimensions of FS ASEMG signals and FP ASEMG signals distributed in two different regions,and its error rate based on Bayes decision was no more than 2.26%.Therefore,the fractal dimension is an appropriate feature by which an FS ASEMG signal is distinguished from an FP ASEMG signal.展开更多
After some permutation of conjugate quadrature filter, new conjugate quadrature filters can be derived. In terms of this permutation, an approach is developed for constructing compactly supported bivariate orthogonal ...After some permutation of conjugate quadrature filter, new conjugate quadrature filters can be derived. In terms of this permutation, an approach is developed for constructing compactly supported bivariate orthogonal wavelets from univariate orthogonal wavelets. Non-separable orthogonal wavelets can be achieved. To demonstrate this method, an example is given.展开更多
This paper presents a supervised classification method of sonar image, which takes advantages of both multi-fractal theory and wavelet analysis. In the process of feature extraction, image transformation and wavelet d...This paper presents a supervised classification method of sonar image, which takes advantages of both multi-fractal theory and wavelet analysis. In the process of feature extraction, image transformation and wavelet decomposition are combined and a feature set based on multi-fractal dimension is obtained. In the part of classifier construction, the Learning Vector Quantization (LVQ) network is adopted as a classifier. Experiments of sonar image classification were carried out with satisfactory results, which verify the effectiveness of this method.展开更多
An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learnin...An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learning ability brought about by the traditional models. Based on the operational data provided by a regional power grid in the south of China, the method was used in the actual short term load forecasting. The results show that the average time cost of the proposed method in the experiment process is reduced by 12.2 s, and the precision of the proposed method is increased by 3.43% compared to the traditional wavelet network. Consequently, the improved wavelet neural network forecasting model is better than the traditional wavelet neural network forecasting model in both forecasting effect and network function.展开更多
The existence of approximate inertial manifold Using wavelet to Burgers' equation, and numerical solution under multiresolution analysis with the low modes were studied. It is shown that the Burgers' equation ...The existence of approximate inertial manifold Using wavelet to Burgers' equation, and numerical solution under multiresolution analysis with the low modes were studied. It is shown that the Burgers' equation has a good localization property of the numerical solution distinguishably.展开更多
The concept of aggregated signal is introduced. Quantitatively, an aggregated signal can be defined as the scalar signal: it accumulates in its own variations only those spectral components that are presented simultan...The concept of aggregated signal is introduced. Quantitatively, an aggregated signal can be defined as the scalar signal: it accumulates in its own variations only those spectral components that are presented simultaneously in each scalar time series of the multidimensional signal to be analyzed. Moreover, an algorithm of aggregation is proposed to suppress the spectral components that are present in any of the scalar components but absent in others (these components can be called local disturbance signals, for instance of technogenic nature). The main purpose of constructing the aggregated signal is to make clearer the common tendency of low-frequency data-flow in geophysical networks, which indicates an increase in collective behavior.It is known that almost all models of the process of earthquake preparation have pointed out an increase in collective behavior of components of geophysical fields in the region of preparation when the coming geocatastrophe has entered its long- and mid-term stages.展开更多
Continuous wavelet transform is employed to detect singularities in 2-D signals by tracking modulus maxima along maxima lines and particularly applied to microcalcification detection in mammograms. The microcalcificat...Continuous wavelet transform is employed to detect singularities in 2-D signals by tracking modulus maxima along maxima lines and particularly applied to microcalcification detection in mammograms. The microcalcifications are modeled as smoothed positive impulse functions. Other target property detection can be performed by adjusting its mathematical model. In this application, the general modulus maximum and its scale of each singular point are detected and statistically analyzed locally in its neighborhood. The diagnosed microcalcification cluster results are compared with health tissue results, showing that general modulus maxima can serve as a suspicious spot detection tool with the detection performance no significantly sensitive to the breast tissue background properties. Performed fractal analysis of selected singularities supports the statistical findings. It is important to select the suitable computation parameters-thresholds of magnitude, argument and frequency range-in accordance to mathematical description of the target property as well as spatial and numerical resolution of the analyzed signal. The tests are performed on a set of images with empirically selected parameters for 200 μm/pixel spatial and 8 bits/pixel numerical resolution, appropriate for detection of the suspicious spots in a mammogram. The results show that the magnitude of a singularity general maximum can play a significant role in the detection of microcalcification, while zooming into a cluster in image finer spatial resolution both magnitude of general maximum and the spatial distribution of the selected set of singularities may lead to the breast abnormality characterization.展开更多
In this paper, we propose a new method for very low bit-rate video coding that combines H.264/AVC standard and two-dimensional discrete wavelet transform. In this method, first a two dimensional wavelet transform is a...In this paper, we propose a new method for very low bit-rate video coding that combines H.264/AVC standard and two-dimensional discrete wavelet transform. In this method, first a two dimensional wavelet transform is applied on each video frame independently to extract the low frequency components for each frame and then the low frequency parts of all frames are coded using H.264/AVC codec. On the other hand, the high frequency parts of the video frames are coded by Run Length Coding algorithm, after applying a threshold to neglect the low value coefficients. Experiments show that our proposed method can achieve better rate-distortion performance at very low bit-rate applications below 16 kbits/s compared to applying H.264/AVC standard directly to all frames. Applications of our proposed video coding technique include video telephony, video-conferencing, transmitting or receiving video over half-rate traffic channels of GSM networks.展开更多
A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1,-1] and its application in the fusion of multi-spectral image are presented. Many 4×4 filter banks are de...A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1,-1] and its application in the fusion of multi-spectral image are presented. Many 4×4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform.展开更多
In this paper, a large class of n dimensional orthogonal and biorthognal wavelet filters (lowpass and highpass) are presented in explicit expression. We also characterize orthogonal filters with linear phase in this c...In this paper, a large class of n dimensional orthogonal and biorthognal wavelet filters (lowpass and highpass) are presented in explicit expression. We also characterize orthogonal filters with linear phase in this case. Some examples are also given, including non separable orhogonal and biorthogonal filters with linear phase.展开更多
We propose a complete parameterization presentation of the 3-channelbivariate non-separable orthogonal FIR filter, and describe the sufficient condition ofgenerating continuous wavelet bases. Given the results above, ...We propose a complete parameterization presentation of the 3-channelbivariate non-separable orthogonal FIR filter, and describe the sufficient condition ofgenerating continuous wavelet bases. Given the results above, a non-separable,compactly supported, orthogonal, continuous parameterized bivariate wavelet bank is setup here.展开更多
基金Project supported by the National Natural Sciences Foundation of China(No.10432030).
文摘A three-dimensional analysis of a simply-supported functionally graded rectangular plate with an arbitrary distribution of material properties is made using a simple and effective method based on the Haar wavelet. With good features in treating singularities, Haar series solution converges rapidly for arbitrary distributions, especially for the case where the material properties change rapidly in some regions. Through numerical examples the influences of the ratio of material constants on the top and bottom surfaces and different material gradient distributions on the structural response of the plate to mechanical stimuli are studied.
基金The National Natural Science Foundation of China(No.60171006)the National Basic Research Programof China (973 Pro-gram) (No.2005CB724303).
文摘Surface electromyogram （EMG） signals were identified by fractal dimension.Two patterns of surface EMG signals were acquired from 30 healthy volunteers＇ right forearm flexor respectively in the process of forearm supination （FS） and forearm pronation （FP）.After the raw action surface EMG （ASEMG） signal was decomposed into several sub-signals with wavelet packet transform （WPT）,five fractal dimensions were respectively calculated from the raw signal and four sub-signals by the method based on fuzzy self-similarity.The results show that calculated from the sub-signal in the band 0 to 125 Hz,the fractal dimensions of FS ASEMG signals and FP ASEMG signals distributed in two different regions,and its error rate based on Bayes decision was no more than 2.26%.Therefore,the fractal dimension is an appropriate feature by which an FS ASEMG signal is distinguished from an FP ASEMG signal.
基金This research was partially supported by National Natural Science Foundation of China (10371033 60403011).
文摘After some permutation of conjugate quadrature filter, new conjugate quadrature filters can be derived. In terms of this permutation, an approach is developed for constructing compactly supported bivariate orthogonal wavelets from univariate orthogonal wavelets. Non-separable orthogonal wavelets can be achieved. To demonstrate this method, an example is given.
文摘This paper presents a supervised classification method of sonar image, which takes advantages of both multi-fractal theory and wavelet analysis. In the process of feature extraction, image transformation and wavelet decomposition are combined and a feature set based on multi-fractal dimension is obtained. In the part of classifier construction, the Learning Vector Quantization (LVQ) network is adopted as a classifier. Experiments of sonar image classification were carried out with satisfactory results, which verify the effectiveness of this method.
基金Project(50579101) supported by the National Natural Science Foundation of China
文摘An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learning ability brought about by the traditional models. Based on the operational data provided by a regional power grid in the south of China, the method was used in the actual short term load forecasting. The results show that the average time cost of the proposed method in the experiment process is reduced by 12.2 s, and the precision of the proposed method is increased by 3.43% compared to the traditional wavelet network. Consequently, the improved wavelet neural network forecasting model is better than the traditional wavelet neural network forecasting model in both forecasting effect and network function.
文摘The existence of approximate inertial manifold Using wavelet to Burgers' equation, and numerical solution under multiresolution analysis with the low modes were studied. It is shown that the Burgers' equation has a good localization property of the numerical solution distinguishably.
文摘The concept of aggregated signal is introduced. Quantitatively, an aggregated signal can be defined as the scalar signal: it accumulates in its own variations only those spectral components that are presented simultaneously in each scalar time series of the multidimensional signal to be analyzed. Moreover, an algorithm of aggregation is proposed to suppress the spectral components that are present in any of the scalar components but absent in others (these components can be called local disturbance signals, for instance of technogenic nature). The main purpose of constructing the aggregated signal is to make clearer the common tendency of low-frequency data-flow in geophysical networks, which indicates an increase in collective behavior.It is known that almost all models of the process of earthquake preparation have pointed out an increase in collective behavior of components of geophysical fields in the region of preparation when the coming geocatastrophe has entered its long- and mid-term stages.
文摘Continuous wavelet transform is employed to detect singularities in 2-D signals by tracking modulus maxima along maxima lines and particularly applied to microcalcification detection in mammograms. The microcalcifications are modeled as smoothed positive impulse functions. Other target property detection can be performed by adjusting its mathematical model. In this application, the general modulus maximum and its scale of each singular point are detected and statistically analyzed locally in its neighborhood. The diagnosed microcalcification cluster results are compared with health tissue results, showing that general modulus maxima can serve as a suspicious spot detection tool with the detection performance no significantly sensitive to the breast tissue background properties. Performed fractal analysis of selected singularities supports the statistical findings. It is important to select the suitable computation parameters-thresholds of magnitude, argument and frequency range-in accordance to mathematical description of the target property as well as spatial and numerical resolution of the analyzed signal. The tests are performed on a set of images with empirically selected parameters for 200 μm/pixel spatial and 8 bits/pixel numerical resolution, appropriate for detection of the suspicious spots in a mammogram. The results show that the magnitude of a singularity general maximum can play a significant role in the detection of microcalcification, while zooming into a cluster in image finer spatial resolution both magnitude of general maximum and the spatial distribution of the selected set of singularities may lead to the breast abnormality characterization.
文摘In this paper, we propose a new method for very low bit-rate video coding that combines H.264/AVC standard and two-dimensional discrete wavelet transform. In this method, first a two dimensional wavelet transform is applied on each video frame independently to extract the low frequency components for each frame and then the low frequency parts of all frames are coded using H.264/AVC codec. On the other hand, the high frequency parts of the video frames are coded by Run Length Coding algorithm, after applying a threshold to neglect the low value coefficients. Experiments show that our proposed method can achieve better rate-distortion performance at very low bit-rate applications below 16 kbits/s compared to applying H.264/AVC standard directly to all frames. Applications of our proposed video coding technique include video telephony, video-conferencing, transmitting or receiving video over half-rate traffic channels of GSM networks.
基金the National Natural Science Foundation of China (Grant No. 10477007)Natural Science Foundation of Hubei Province (Grant No. 2006ABA015)the Key Project of Hubei Provincial Department of Education (Grant No. D200510004)
文摘A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1,-1] and its application in the fusion of multi-spectral image are presented. Many 4×4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform.
文摘In this paper, a large class of n dimensional orthogonal and biorthognal wavelet filters (lowpass and highpass) are presented in explicit expression. We also characterize orthogonal filters with linear phase in this case. Some examples are also given, including non separable orhogonal and biorthogonal filters with linear phase.
文摘We propose a complete parameterization presentation of the 3-channelbivariate non-separable orthogonal FIR filter, and describe the sufficient condition ofgenerating continuous wavelet bases. Given the results above, a non-separable,compactly supported, orthogonal, continuous parameterized bivariate wavelet bank is setup here.
