In this paper an improved multi_scale estimation method of signal is gaven.The detail signals on each scale are further more decomposed with wavelet transform.The subdetail signals and subsmoothing signals are process...In this paper an improved multi_scale estimation method of signal is gaven.The detail signals on each scale are further more decomposed with wavelet transform.The subdetail signals and subsmoothing signals are processed with different threshold respectively. The smoothing signals on the coarsest scale are processed with Kalman fitering and reconstructed with the detail signal on each scale.At last the signal estimate value on the original scale is obtained.展开更多
An embedded underground coal seam carries channel waves of low seismic velocity along a stratigraphic rock-coal-rock sequence.In a homogeneous and isotropic seam, seismic waves propagate as trapped waves within the se...An embedded underground coal seam carries channel waves of low seismic velocity along a stratigraphic rock-coal-rock sequence.In a homogeneous and isotropic seam, seismic waves propagate as trapped waves within the seam, which leads to propagation of channel waves.We describe how to set up a field test for transmission in order to acquire channel waves in a coal seam.Because channel wave signals are non-stationary in their frequencies and amplitudes, a necessary velocity spectrum and wavelet transformation analysis are applied to interpret the characteristics of channel waves.The advantage of using a wavelet transformation is that different resolutions can be obtained at different times and different frequencies.According to analysis of the seismic signals acquired in the S7 sensor hole, it was clearly shown that the characteristics of channel waves are lower frequencies and attenuation which can guide an effective wave for detecting voids, boundaries and faults in coal seams with strong roofs and floors.展开更多
Let E= .A measurable function v is called an E- waveletmultiplier if (vψ) is an E-wavelet whenever ψ is an E-wavelet. Some characterizations and applications of E-wavelet multiplier were considered in [1]. In this p...Let E= .A measurable function v is called an E- waveletmultiplier if (vψ) is an E-wavelet whenever ψ is an E-wavelet. Some characterizations and applications of E-wavelet multiplier were considered in [1]. In this paper, we give some other applications of E-wavelet multiplier, and prove that the set of all MRA E-wavelets is arcwise connected.展开更多
The critical technical problem of underwater bottom object detection is founding a stable feature space for echo signals classification. The past literatures more focus on the characteristics of object echoes in featu...The critical technical problem of underwater bottom object detection is founding a stable feature space for echo signals classification. The past literatures more focus on the characteristics of object echoes in feature space and reverberation is only treated as interference. In this paper, reverberation is considered as a kind of signal with steady characteristic, and the clustering of reverberation in frequency discrete wavelet transform （FDWT） feature space is studied. In order to extract the identifying information of echo signals, feature compression and cluster analysis are adopted in this paper, and the criterion of separability between object echoes and reverberation is given. The experimental data processing results show that reverberation has steady pattern in FDWT feature space which differs from that of object echoes. It is proven that there is separability between reverberation and object echoes.展开更多
文摘In this paper an improved multi_scale estimation method of signal is gaven.The detail signals on each scale are further more decomposed with wavelet transform.The subdetail signals and subsmoothing signals are processed with different threshold respectively. The smoothing signals on the coarsest scale are processed with Kalman fitering and reconstructed with the detail signal on each scale.At last the signal estimate value on the original scale is obtained.
基金Project B2532532 supported by the U.S. Mine Safety and Health Administration
文摘An embedded underground coal seam carries channel waves of low seismic velocity along a stratigraphic rock-coal-rock sequence.In a homogeneous and isotropic seam, seismic waves propagate as trapped waves within the seam, which leads to propagation of channel waves.We describe how to set up a field test for transmission in order to acquire channel waves in a coal seam.Because channel wave signals are non-stationary in their frequencies and amplitudes, a necessary velocity spectrum and wavelet transformation analysis are applied to interpret the characteristics of channel waves.The advantage of using a wavelet transformation is that different resolutions can be obtained at different times and different frequencies.According to analysis of the seismic signals acquired in the S7 sensor hole, it was clearly shown that the characteristics of channel waves are lower frequencies and attenuation which can guide an effective wave for detecting voids, boundaries and faults in coal seams with strong roofs and floors.
基金Supported by the NSF of China(60272042)Supported by the NSF of Henan University of China(XK03YBJS008)
文摘Let E= .A measurable function v is called an E- waveletmultiplier if (vψ) is an E-wavelet whenever ψ is an E-wavelet. Some characterizations and applications of E-wavelet multiplier were considered in [1]. In this paper, we give some other applications of E-wavelet multiplier, and prove that the set of all MRA E-wavelets is arcwise connected.
基金Supported by the National Natural Science Foundation of China, under Grant No.51279033.
文摘The critical technical problem of underwater bottom object detection is founding a stable feature space for echo signals classification. The past literatures more focus on the characteristics of object echoes in feature space and reverberation is only treated as interference. In this paper, reverberation is considered as a kind of signal with steady characteristic, and the clustering of reverberation in frequency discrete wavelet transform （FDWT） feature space is studied. In order to extract the identifying information of echo signals, feature compression and cluster analysis are adopted in this paper, and the criterion of separability between object echoes and reverberation is given. The experimental data processing results show that reverberation has steady pattern in FDWT feature space which differs from that of object echoes. It is proven that there is separability between reverberation and object echoes.
