Based on explanation of wavelet fractal compression method, the significance of introducing wavelet decomposition into conventional fractal compression method is deeply investigated from the point of theoretical and p...Based on explanation of wavelet fractal compression method, the significance of introducing wavelet decomposition into conventional fractal compression method is deeply investigated from the point of theoretical and practical view. The result of study can be regarded as valuable guidelines for taking advantages of wavelet transform to develop more effective image compression algorithm.展开更多
Floodwater utilization is an important content in flood management. Controlling the limit water level of reservoir by stage is one of important contents in the management of multi-purpose reservoir’s floodwater utili...Floodwater utilization is an important content in flood management. Controlling the limit water level of reservoir by stage is one of important contents in the management of multi-purpose reservoir’s floodwater utilization for the sake of more benefits, and reasonable division of stage in flood season is precondition of controlling the limit water level by stage. On the background of Three Gorges Reservoir floodwater utilization management and on the foundation of self-similarity of hydrological series, determining the number of flood season staged in base of conventional statistical method, choosing the Db4 wavelet and Mallat algorithm, the computation mode of wavelet fractal dimension estimation method is proposed and each stage’s fractal dimension is computed, then the final flood season staged is obtained. The results demonstrate the stages of Three Gorges Reservoir determined by using wavelet fractal dimension method are consistent with that from conventional method, but the fractal dimension results by former method are easier, more stable and objective which ensures the feasibility of the wavelet fractal dimension method applying in flood season staged. The obtained results are the base of deep coping with floodwater utilization management, also are the decision-making gist for the flood forecast, flood control and water allocation reasonably of Three Gorges Reservoir.展开更多
A new method based on the combining of the wavelet theory with the fractal theory and named wavelet fractal peak position method (WFPPM) is introduced to ex-tract the number of the components and the relevant peak pos...A new method based on the combining of the wavelet theory with the fractal theory and named wavelet fractal peak position method (WFPPM) is introduced to ex-tract the number of the components and the relevant peak positions from overlapping signals in chemistry. The over-lapping signal is first transformed into continuous wavelet transform value of time domain in certain dilation range via continuous wavelet transform (CWT), and then changed into capacity dimensions (Dc). The number of the components and the relevant positions of overlapping peaks can be iden-tified easily according to the change of Dc. An investigation concerning the influence of different dilation ranges on the peak positions extracted by WFPPM is also provided. Stud-ies show that the WFPPM is an efficient tool for extracting the peak positions and identifying the number of peaks from unresolved signals, even when this kind of overlapping is significantly serious. Relative errors of less than 1.0% in peak positions are found when WFPPM is used in the pro- cessing of the cadmium(Ⅱ)-indium(Ⅲ) mixture system. The analytical results demonstrate that the desired peak positions can be extracted conveniently, accurately and rapidly from an unresolved signal via WFPPM. Tremendous developing and applications based on currently reported WFPPM in extracting overlapping signals would be expected in the near future.展开更多
In this paper, we study on the application of radical B-spline wavelet scaling function in fractal function approximation system. The paper proposes a wavelet-based fractal function approximation algorithm in which th...In this paper, we study on the application of radical B-spline wavelet scaling function in fractal function approximation system. The paper proposes a wavelet-based fractal function approximation algorithm in which the coefficients can be determined by solving a convex quadraticprogramming problem. And the experiment result shows that the approximation error of this algorithm is smaller than that of the polynomial-based fractal function approximation. This newalgorithm exploits the consistency between fractal and scaling function in multi-scale and multiresolution, has a better approximation effect and high potential in data compression, especially inimage compression.展开更多
Based on the mechanisms underlying the performance of fractal and Discrete Wavelet Transform(DWT), one method using fractal-based self-quantization coding way to code different subband coefficients of DWT is presented...Based on the mechanisms underlying the performance of fractal and Discrete Wavelet Transform(DWT), one method using fractal-based self-quantization coding way to code different subband coefficients of DWT is presented. Within this method finer coefficients are fractal encoded according to the successive coarser ones. Self-similarities inherent between parent and their children at the same spatial location of the adjacent scales of similar orientation are exploited to predict variation of information across wavelet scales. On the other hand, with respect to Human Visual System(HVS) model, we assign different error thresholds to different decomposition scales, and different shape of range blocks to different orientations of the same scale, by which the perceptually lossless high compression ratio can be achieved and the matching processing can be quickened dramatically.展开更多
This paper presents some results of the relation between wavelet transform and fractal transform. The wavelet transform of the attractor of fractal transform posseses translational and scale invariance. So we speed th...This paper presents some results of the relation between wavelet transform and fractal transform. The wavelet transform of the attractor of fractal transform posseses translational and scale invariance. So we speed the fractal image encoding by testing the invariance of the wavelet transform appropriate for image encoding. The classfication scheme of range blocks by wavelet transform is given in this paper.展开更多
In this paper,a novel face recognition method,named as wavelet-curvelet-fractal technique,is proposed. Based on the similarities embedded in the images,we propose to utilize the wave-let-curvelet-fractal technique to ...In this paper,a novel face recognition method,named as wavelet-curvelet-fractal technique,is proposed. Based on the similarities embedded in the images,we propose to utilize the wave-let-curvelet-fractal technique to extract facial features. Thus we have the wavelet’s details in diagonal,vertical,and horizontal directions,and the eight curvelet details at different angles. Then we adopt the Euclidean minimum distance classifier to recognize different faces. Extensive comparison tests on dif-ferent data sets are carried out,and higher recognition rate is obtained by the proposed technique.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
The turbulence data are decomposed to multi-scales and its respective fractal dimensions are computed. The conclusions are drawn from investigating the variation of fractal dimensions. With the level of decomposition ...The turbulence data are decomposed to multi-scales and its respective fractal dimensions are computed. The conclusions are drawn from investigating the variation of fractal dimensions. With the level of decomposition increasing, the low-frequency part extracted from the turbulence signals tends to be simple and smooth, the dimensions decrease; the high-frequency part shows complex, the dimensions are fixed, about 1.70 on the average, which indicates clear self-similarity characteristics.展开更多
An important new development in hydrological data analysis in the last decade is the application of wavelet analysis. Here, wave- let theory is used to study the complexity and multi-scale periodicity of the hydrologi...An important new development in hydrological data analysis in the last decade is the application of wavelet analysis. Here, wave- let theory is used to study the complexity and multi-scale periodicity of the hydrological time series of the Dalai Lake Basin in In- ner Mongolia. Two large rivers, the Kelulun and the Wurxun, are the main inflows to Dalai Lake, which is currently shrinking. The annual and monthly flows of the Kelultm River are shown to vary more than those of the Wurxun River, and the monthly flows of the two rivers vary much more than their annual flows. Db5 wavelets are shown to be more suitable for annual flow cal- culations, whereas Db4 wavelets are more suitable for monthly flow calculations. Multi-scale wavelet analysis of the annual and monthly flows of the Kelulun and Wurxun rivers shows that the variation of the two rivers is similar and has a 25-year cycle, 12 years of wet and 12 years of drought periods, and our results show that both rivers are expected to transition into a wet period be- ginning in 2012. Therefore, the Dalai Lake Basin, which has been in a drought period since 2000, is expected to gradually transit into a wet period from 2012 onward.展开更多
Using the Walsh-Fourier transform, we give a construction of compactly supported nonstationary dyadic wavelets on the positive half-line. The masks of these wavelets are the Walsh polynomials defined by finite sets of...Using the Walsh-Fourier transform, we give a construction of compactly supported nonstationary dyadic wavelets on the positive half-line. The masks of these wavelets are the Walsh polynomials defined by finite sets of parameters. Application to compression of fractal functions are also discussed.展开更多
The non-linear dynamic theory brought a new method for recognizing and predicting complex non-linear dynamic behaviors. The non-linear behavior of vibration signals can be described by using fractal dimension quantita...The non-linear dynamic theory brought a new method for recognizing and predicting complex non-linear dynamic behaviors. The non-linear behavior of vibration signals can be described by using fractal dimension quantitatively. In this paper, a fractal dimension calculation method for discrete signals in the fractal theory was applied to extract the fractal dimension feature vectors and classified various fault types. Based on the wavelet packet transform, the energy feature vectors were extracted after the vibration signal was decomposed and reconstructed. Then, a wavelet neural network was used to recognize the mechanical faults. Finally, the fault diagnosis for a wind power system was taken as an example to show the method's feasibility.展开更多
Clustering algorithms in feature space are important methods in image segmentation. The choice of the effective feature parameters and the construction of the clustering method are key problems encountered with cluste...Clustering algorithms in feature space are important methods in image segmentation. The choice of the effective feature parameters and the construction of the clustering method are key problems encountered with clustering algorithms. In this paper, the multifractal dimensions are chosen as the segmentation feature parameters which are extracted from original image and wavelet-transformed image. SOM (Self-Organizing Map) network is applied to cluster the segmentation feature parameters. The experiment shows that the performance of the presented algorithm is very good.展开更多
Based on the whitening property of wavelet transformation for 1/f noise, this paper addresses the problem of detecting deterministic signals in the presence of 1/f fractal noise. The transfer function of whitening fil...Based on the whitening property of wavelet transformation for 1/f noise, this paper addresses the problem of detecting deterministic signals in the presence of 1/f fractal noise. The transfer function of whitening filter is provided as well as the condition for whitening. The receiver structure based on Karhunen-Loeve expansion and the decision rule are also given. Finally performance of the detector is analyzed.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
A rate adaptive multi-band ultra-wideband (UWB) system based on the quadrature fractal modulation (QFM) scheme was proposed.Exploring the use of homogeneous signals as modulating waveforms in UWB system,the signal wit...A rate adaptive multi-band ultra-wideband (UWB) system based on the quadrature fractal modulation (QFM) scheme was proposed.Exploring the use of homogeneous signals as modulating waveforms in UWB system,the signal within each 528MHz sub-band was divided into 8 different frequency bandwidths using wavelets transform and these data sequences to be transmitted were embedded into homogeneous waveforms.It is found that the use of homogeneous signals in such UWB system is quite feasible,leadings to a novel multi-rate diversity strategy.Within each 528MHz sub-band,the UWB-QFM system can provide much higher data rates than that of the UWB orthogonal frequency division multiplexing (OFDM) system.Simulation results also show that the bit error rate (BER) performance of the UWB-QFM system achieves a greatly improvement over existing UWB-OFDM system.Due to the fractal properties of the homogeneous signals,these data sequences to be transmitted can be recovered using arbitrarily short receiver signal.展开更多
Stochastic noises of fiber optic gyroscope （FOG） mainly contain white noise and fractal noise whose long-term dependent component causes FOG a rather slow drift. In order to eliminate this component, a two-step filt...Stochastic noises of fiber optic gyroscope （FOG） mainly contain white noise and fractal noise whose long-term dependent component causes FOG a rather slow drift. In order to eliminate this component, a two-step filtering methodology is proposed. Firstly, fractional differencing （FD） method is introduced to trans-form fractal noise into fractional white noise based on the estima-tion of Hurst exponent for long-term dependent fractal process, which together with the existing white noise make up of a gener-alized white noise. Further, an improved denoising algorithm of wavelet maxima is developed to suppress the generalized white noise. Experimental results show that the basic noise terms of FOG greatly decrease, and especially the slow drift is restrained effectively. The proposed methodology provides a promising ap-proach for filtering long-term dependent fractal noise.展开更多
基金This project is supported by the National Natural Science Foundation of China (No. 69774030) Foundation for University Key Teacher by the Ministry of Education.
文摘Based on explanation of wavelet fractal compression method, the significance of introducing wavelet decomposition into conventional fractal compression method is deeply investigated from the point of theoretical and practical view. The result of study can be regarded as valuable guidelines for taking advantages of wavelet transform to develop more effective image compression algorithm.
基金Project supported bythe National Nature Science Foundation of China(No.6057407)
文摘Floodwater utilization is an important content in flood management. Controlling the limit water level of reservoir by stage is one of important contents in the management of multi-purpose reservoir’s floodwater utilization for the sake of more benefits, and reasonable division of stage in flood season is precondition of controlling the limit water level by stage. On the background of Three Gorges Reservoir floodwater utilization management and on the foundation of self-similarity of hydrological series, determining the number of flood season staged in base of conventional statistical method, choosing the Db4 wavelet and Mallat algorithm, the computation mode of wavelet fractal dimension estimation method is proposed and each stage’s fractal dimension is computed, then the final flood season staged is obtained. The results demonstrate the stages of Three Gorges Reservoir determined by using wavelet fractal dimension method are consistent with that from conventional method, but the fractal dimension results by former method are easier, more stable and objective which ensures the feasibility of the wavelet fractal dimension method applying in flood season staged. The obtained results are the base of deep coping with floodwater utilization management, also are the decision-making gist for the flood forecast, flood control and water allocation reasonably of Three Gorges Reservoir.
基金This work was supported by the National Natural Science Foundation of China (Grant No. 29975033) and Guangdong Provincial Natural Science Foundation (Grant No. 001237).
文摘A new method based on the combining of the wavelet theory with the fractal theory and named wavelet fractal peak position method (WFPPM) is introduced to ex-tract the number of the components and the relevant peak positions from overlapping signals in chemistry. The over-lapping signal is first transformed into continuous wavelet transform value of time domain in certain dilation range via continuous wavelet transform (CWT), and then changed into capacity dimensions (Dc). The number of the components and the relevant positions of overlapping peaks can be iden-tified easily according to the change of Dc. An investigation concerning the influence of different dilation ranges on the peak positions extracted by WFPPM is also provided. Stud-ies show that the WFPPM is an efficient tool for extracting the peak positions and identifying the number of peaks from unresolved signals, even when this kind of overlapping is significantly serious. Relative errors of less than 1.0% in peak positions are found when WFPPM is used in the pro- cessing of the cadmium(Ⅱ)-indium(Ⅲ) mixture system. The analytical results demonstrate that the desired peak positions can be extracted conveniently, accurately and rapidly from an unresolved signal via WFPPM. Tremendous developing and applications based on currently reported WFPPM in extracting overlapping signals would be expected in the near future.
文摘In this paper, we study on the application of radical B-spline wavelet scaling function in fractal function approximation system. The paper proposes a wavelet-based fractal function approximation algorithm in which the coefficients can be determined by solving a convex quadraticprogramming problem. And the experiment result shows that the approximation error of this algorithm is smaller than that of the polynomial-based fractal function approximation. This newalgorithm exploits the consistency between fractal and scaling function in multi-scale and multiresolution, has a better approximation effect and high potential in data compression, especially inimage compression.
文摘Based on the mechanisms underlying the performance of fractal and Discrete Wavelet Transform(DWT), one method using fractal-based self-quantization coding way to code different subband coefficients of DWT is presented. Within this method finer coefficients are fractal encoded according to the successive coarser ones. Self-similarities inherent between parent and their children at the same spatial location of the adjacent scales of similar orientation are exploited to predict variation of information across wavelet scales. On the other hand, with respect to Human Visual System(HVS) model, we assign different error thresholds to different decomposition scales, and different shape of range blocks to different orientations of the same scale, by which the perceptually lossless high compression ratio can be achieved and the matching processing can be quickened dramatically.
文摘This paper presents some results of the relation between wavelet transform and fractal transform. The wavelet transform of the attractor of fractal transform posseses translational and scale invariance. So we speed the fractal image encoding by testing the invariance of the wavelet transform appropriate for image encoding. The classfication scheme of range blocks by wavelet transform is given in this paper.
基金Supported by the College of Heilongjiang Province, Electronic Engineering Key Lab Project dzzd200602Heilongjiang Province Educational Bureau Scientific Technology Important Project 11531z18
文摘In this paper,a novel face recognition method,named as wavelet-curvelet-fractal technique,is proposed. Based on the similarities embedded in the images,we propose to utilize the wave-let-curvelet-fractal technique to extract facial features. Thus we have the wavelet’s details in diagonal,vertical,and horizontal directions,and the eight curvelet details at different angles. Then we adopt the Euclidean minimum distance classifier to recognize different faces. Extensive comparison tests on dif-ferent data sets are carried out,and higher recognition rate is obtained by the proposed technique.
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 is supported by the Key Project of National Natural Science Foundation of China (No.40035010
文摘The turbulence data are decomposed to multi-scales and its respective fractal dimensions are computed. The conclusions are drawn from investigating the variation of fractal dimensions. With the level of decomposition increasing, the low-frequency part extracted from the turbulence signals tends to be simple and smooth, the dimensions decrease; the high-frequency part shows complex, the dimensions are fixed, about 1.70 on the average, which indicates clear self-similarity characteristics.
基金supported by the project"Ecohydrological process modeling of Dalai Lake Basin under different grazing system" granted by the National Natural Science Foundation of China (Grant No. 51169011)
文摘An important new development in hydrological data analysis in the last decade is the application of wavelet analysis. Here, wave- let theory is used to study the complexity and multi-scale periodicity of the hydrological time series of the Dalai Lake Basin in In- ner Mongolia. Two large rivers, the Kelulun and the Wurxun, are the main inflows to Dalai Lake, which is currently shrinking. The annual and monthly flows of the Kelultm River are shown to vary more than those of the Wurxun River, and the monthly flows of the two rivers vary much more than their annual flows. Db5 wavelets are shown to be more suitable for annual flow cal- culations, whereas Db4 wavelets are more suitable for monthly flow calculations. Multi-scale wavelet analysis of the annual and monthly flows of the Kelulun and Wurxun rivers shows that the variation of the two rivers is similar and has a 25-year cycle, 12 years of wet and 12 years of drought periods, and our results show that both rivers are expected to transition into a wet period be- ginning in 2012. Therefore, the Dalai Lake Basin, which has been in a drought period since 2000, is expected to gradually transit into a wet period from 2012 onward.
文摘Using the Walsh-Fourier transform, we give a construction of compactly supported nonstationary dyadic wavelets on the positive half-line. The masks of these wavelets are the Walsh polynomials defined by finite sets of parameters. Application to compression of fractal functions are also discussed.
基金Sponsored by the National Science Foundation (61004118)the Natural Science Foundation Project of CQ CSTC (2011A70007)+1 种基金the Science and Technology Research Project of Chongqing Municipal Education Commission (KJ120422)the Science Foundation Project of Chongqing Jiaotong University Open Research Fund of Key Laboratory of Bridge Structural Engineering of Chongqing Jiaotong University (CQSLBF-Y11-5)
文摘The non-linear dynamic theory brought a new method for recognizing and predicting complex non-linear dynamic behaviors. The non-linear behavior of vibration signals can be described by using fractal dimension quantitatively. In this paper, a fractal dimension calculation method for discrete signals in the fractal theory was applied to extract the fractal dimension feature vectors and classified various fault types. Based on the wavelet packet transform, the energy feature vectors were extracted after the vibration signal was decomposed and reconstructed. Then, a wavelet neural network was used to recognize the mechanical faults. Finally, the fault diagnosis for a wind power system was taken as an example to show the method's feasibility.
文摘Clustering algorithms in feature space are important methods in image segmentation. The choice of the effective feature parameters and the construction of the clustering method are key problems encountered with clustering algorithms. In this paper, the multifractal dimensions are chosen as the segmentation feature parameters which are extracted from original image and wavelet-transformed image. SOM (Self-Organizing Map) network is applied to cluster the segmentation feature parameters. The experiment shows that the performance of the presented algorithm is very good.
文摘Based on the whitening property of wavelet transformation for 1/f noise, this paper addresses the problem of detecting deterministic signals in the presence of 1/f fractal noise. The transfer function of whitening filter is provided as well as the condition for whitening. The receiver structure based on Karhunen-Loeve expansion and the decision rule are also given. Finally performance of the detector is analyzed.
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.
基金National Natural Science Fund of China(60372097), Beijing Municipal Natural Science Fund(4052021),University IT Research Center Project(INHA UWB-ITRC)Korea, KDDI R&D Labs Co-Project, Japan.
文摘A rate adaptive multi-band ultra-wideband (UWB) system based on the quadrature fractal modulation (QFM) scheme was proposed.Exploring the use of homogeneous signals as modulating waveforms in UWB system,the signal within each 528MHz sub-band was divided into 8 different frequency bandwidths using wavelets transform and these data sequences to be transmitted were embedded into homogeneous waveforms.It is found that the use of homogeneous signals in such UWB system is quite feasible,leadings to a novel multi-rate diversity strategy.Within each 528MHz sub-band,the UWB-QFM system can provide much higher data rates than that of the UWB orthogonal frequency division multiplexing (OFDM) system.Simulation results also show that the bit error rate (BER) performance of the UWB-QFM system achieves a greatly improvement over existing UWB-OFDM system.Due to the fractal properties of the homogeneous signals,these data sequences to be transmitted can be recovered using arbitrarily short receiver signal.
基金supported by Aviation Science Foundation(20070851011).
文摘Stochastic noises of fiber optic gyroscope （FOG） mainly contain white noise and fractal noise whose long-term dependent component causes FOG a rather slow drift. In order to eliminate this component, a two-step filtering methodology is proposed. Firstly, fractional differencing （FD） method is introduced to trans-form fractal noise into fractional white noise based on the estima-tion of Hurst exponent for long-term dependent fractal process, which together with the existing white noise make up of a gener-alized white noise. Further, an improved denoising algorithm of wavelet maxima is developed to suppress the generalized white noise. Experimental results show that the basic noise terms of FOG greatly decrease, and especially the slow drift is restrained effectively. The proposed methodology provides a promising ap-proach for filtering long-term dependent fractal noise.
