Using approximation technique, we introduce the concepts of canonical extension and symmetrio integral for jump process and obtain some results in the chaotic form.
We discuss the linear conjugate boundary value problems on the unit circle and the real axis. We obtain some Fredholm integral equations. Using thess equations we discuss the solvable conditions on these problems and ...We discuss the linear conjugate boundary value problems on the unit circle and the real axis. We obtain some Fredholm integral equations. Using thess equations we discuss the solvable conditions on these problems and we also give a direct method for the extension problems on the real axis.展开更多
When an image, which is decomposed by bi-orthogonal wavelet bases, is reconstructed, some information will be lost at the four edges of the image. At the same time, artificial discontinuities will be introduced. We us...When an image, which is decomposed by bi-orthogonal wavelet bases, is reconstructed, some information will be lost at the four edges of the image. At the same time, artificial discontinuities will be introduced. We use a method called symmetric extension to solve the problem. We only consider the case of the two-band filter banks, and the results can be applied to M-band filter banks. There are only two types of symmetric extension in analysis phrase, namely the whole-sample symmetry (WS), the half-sample symmetry (HS), while there are four types of symmetric extension in synthesis phrase, namely the WS, HS, the whole-sample anti-symmetry (WA), and the half-sample anti-symmetry (HA) respectively. We can select the exact type according to the image length and the filter length, and we will show how to do these. The image can be perfectly reconstructed without any edge effects in this way. Finally, simulation results are reported. Key words edge effect - image compression - wavelet - biorthogonal bases - symmetric extension CLC number TP 37 Foundation item: Supported by the National 863 Project (20021111901010)Biography: Yu Sheng-sheng (1944-), male, Professor, research direction: multimedia information processing, SAN.展开更多
In this paper, a novel method that integrates the improved empirical mode decomposition （EMD） and signal energy algorithm is proposed to estimate the dominant oscillation parameters and corresponding mode shape. Fir...In this paper, a novel method that integrates the improved empirical mode decomposition （EMD） and signal energy algorithm is proposed to estimate the dominant oscillation parameters and corresponding mode shape. Firstly, the EMD with symmetrical extrema extension （SEE） is utilized to decompose the measured data from wide area measurement system （WAMS） into a finite set of intrinsic mode functions （1MFs）. Then, the signal energy algorithm is used to calculate the approximate oscillation parameters of the IMFs. The nodes involved the dominant oscillation mode are classified based on the calculated frequency and reasonable threshold. Furthermore, for the dominant oscillation mode, the IMF with maximum mean amplitude is defined as the reference. Next, the relative phases （RPs） between the reference IMF and other 1MFs are calculated in order to identify the negative and positive oscillation groups. According to the values of RPs, the coherent group and corresponding node contribution factor （NCF） can be identified, and the dominant approximate mode shape （AMS） can also be determined. The efficiency of the proposed approach is tested by applying it to synthetic signal and measured data from the simulation model.展开更多
基金Supported in part by National Natural Science Foundation of China.
文摘Using approximation technique, we introduce the concepts of canonical extension and symmetrio integral for jump process and obtain some results in the chaotic form.
基金Supported by the National Natural Science Foundation of China (10471107)
文摘We discuss the linear conjugate boundary value problems on the unit circle and the real axis. We obtain some Fredholm integral equations. Using thess equations we discuss the solvable conditions on these problems and we also give a direct method for the extension problems on the real axis.
文摘When an image, which is decomposed by bi-orthogonal wavelet bases, is reconstructed, some information will be lost at the four edges of the image. At the same time, artificial discontinuities will be introduced. We use a method called symmetric extension to solve the problem. We only consider the case of the two-band filter banks, and the results can be applied to M-band filter banks. There are only two types of symmetric extension in analysis phrase, namely the whole-sample symmetry (WS), the half-sample symmetry (HS), while there are four types of symmetric extension in synthesis phrase, namely the WS, HS, the whole-sample anti-symmetry (WA), and the half-sample anti-symmetry (HA) respectively. We can select the exact type according to the image length and the filter length, and we will show how to do these. The image can be perfectly reconstructed without any edge effects in this way. Finally, simulation results are reported. Key words edge effect - image compression - wavelet - biorthogonal bases - symmetric extension CLC number TP 37 Foundation item: Supported by the National 863 Project (20021111901010)Biography: Yu Sheng-sheng (1944-), male, Professor, research direction: multimedia information processing, SAN.
文摘In this paper, a novel method that integrates the improved empirical mode decomposition （EMD） and signal energy algorithm is proposed to estimate the dominant oscillation parameters and corresponding mode shape. Firstly, the EMD with symmetrical extrema extension （SEE） is utilized to decompose the measured data from wide area measurement system （WAMS） into a finite set of intrinsic mode functions （1MFs）. Then, the signal energy algorithm is used to calculate the approximate oscillation parameters of the IMFs. The nodes involved the dominant oscillation mode are classified based on the calculated frequency and reasonable threshold. Furthermore, for the dominant oscillation mode, the IMF with maximum mean amplitude is defined as the reference. Next, the relative phases （RPs） between the reference IMF and other 1MFs are calculated in order to identify the negative and positive oscillation groups. According to the values of RPs, the coherent group and corresponding node contribution factor （NCF） can be identified, and the dominant approximate mode shape （AMS） can also be determined. The efficiency of the proposed approach is tested by applying it to synthetic signal and measured data from the simulation model.
