An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packe...An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packet theory to adaptive beamforming, a wavelet packet transform-based adaptive beamforming algorithm (WP-ABF) is proposed . This WP-ABF algorithm uses wavelet packet transform as the preprocessing, and the wavelet packet transformed signal uses least mean square algorithm to implement the ~adaptive beamforming. White noise can be wiped off under wavelet packet transform according to the different characteristics of signal and white under the wavelet packet transform. Theoretical analysis and simulations demonstrate that the proposed WP-ABF algorithm converges faster than the conventional adaptive beamforming algorithm and the wavelet transform-based beamforming algorithm. Simulation results also reveal that the convergence of the algorithm relates closely to the wavelet base and series; that is, the algorithm convergence gets better with the increasing of series, and for the same series of wavelet base the convergence gets better with the increasing of regularity.展开更多
A new adaptive Packet algorithm based on Discrete Cosine harmonic wavelet transform (DCHWT), (DCAHWP) has been proposed. This is realized by the Discrete Cosine Harmonic Wavelet transform (DCHTWT) which exploits the g...A new adaptive Packet algorithm based on Discrete Cosine harmonic wavelet transform (DCHWT), (DCAHWP) has been proposed. This is realized by the Discrete Cosine Harmonic Wavelet transform (DCHTWT) which exploits the good properties of DCT viz., energy compaction (low leakage), frequency resolution and computational simplicity due its real nature, compared to those of DFT and its harmonic wavelet version. Hence the proposed wavelet packet is advantageous both in terms of performance and computational efficiency compared to those of existing DFT harmonic wavelet packet. Further, the new DCAHWP also enjoys the desirable properties of a Harmonic wavelet transform over the time domain WT, viz., built in decimation without any explicit antialiasing filtering and easy interpolation by mere concatenation of different scales in frequency (DCT) domain with out any image rejection filter and with out laborious delay compensation required. Further, the compression by the proposed DCAHWP is much better compared to that by adaptive WP based on Daubechies-2 wavelet (DBAWP). For a compression factor (CF) of 1/8, the ratio of the percentage error energy by proposed DCAHWP to that by DBAWP is about 1/8 and 1/5 for considered 1-D signal and speech signal, respectively. Its compression performance is better than that of DCHWT, both for 1-D and 2-D signals. The improvement is more significant for signals with abrupt changes or images with rapid variations (textures). For compression factor of 1/8, the ratio of the percentage error energy by DCAHWP to that by DCHWT, is about 1/3 and 1/2, for the considered 1-D signal and speech signal, respectively. This factor for an image considered is 2/3 and in particular for a textural image it is 1/5.展开更多
A satellite image adaptive restoration method was developed that avoids ringing artifacts at the image boundary and retains oriented features. The method combines periodic plus smooth image decom- position with comple...A satellite image adaptive restoration method was developed that avoids ringing artifacts at the image boundary and retains oriented features. The method combines periodic plus smooth image decom- position with complex wavelet packet transforms. The framework first decomposes a degraded satellite im- age into the sum of a ＂periodic component＂ and a ＂smooth component＂. The Bayesian method is then used to estimate the modulation transfer function degradation parameters and the noise. The periodic component is deconvoluted using complex wavelet packet transforms with the deconvolution result of the periodic component then combined with the smooth component to get the final recovered result. Tests show that this strategy effectively avoids ringing artifacts while preserving local image details （especially directional tex- tures） without amplifying the noise. Quantitative comparisons illustrate that the results are comparable with previous methods. Another benefit is that this approach can process large satellite images with parallel processing, which is important for practical use.展开更多
One of the major issues with multi-carrier systems is their vulnerability to timing synchronization errors resulting in the loss of time synchronization which causes loss of orientation of incoming data at the receive...One of the major issues with multi-carrier systems is their vulnerability to timing synchronization errors resulting in the loss of time synchronization which causes loss of orientation of incoming data at the receiver. This paper presents an acquisition algorithm to timing recovery using the decision-aided extended Kalman filtering （EKF） technique for nonlinear disturbance channels in a wavelet packet transform-based multicarrier modulation communication system. This timing recovery algorithm gives faster convergence, smaller root mean square （RMS） errors, and better bit error rate （BER） performance than traditional timing recovery methods, such as the phase-locked loop （PLL）, maximum likelihood （ML）, and Kalman filter （KF） methods. Thus, the algorithm is able to handle larger timing errors more reliably and to provide better timing recovery, since the scheme takes into account the nonlinear relationship between the signal samples and timing errors. Simulations for various time-varying channels show that the timing recovery algorithm works well for wavelet packet transform-based multicarrier modulation communication systems.展开更多
We present a new algorithm for adaptive single-pole auto-reclosing of power transmission lines using wavelet packet transform. The db8 wavelet packet decomposes the faulted phase voltage waveform to obtain the coeffic...We present a new algorithm for adaptive single-pole auto-reclosing of power transmission lines using wavelet packet transform. The db8 wavelet packet decomposes the faulted phase voltage waveform to obtain the coefficients of the nodes 257, 259 to 262. An index is then defined from the sum of the energy coefficients of these nodes. By evaluating the index, transient and permanent faults, as well as the secondary arc extinction instant, can be identified. The significant advantage of the proposed algorithm is that it does not need a threshold level and therefore its performance is independent of fault location, line parameters, and operating conditions. Moreover, it can be used in transmission lines with reactor compensation. The proposed method has been successfully tested under a variety of fault conditions on a 400 kV overhead line of the Iranian National Grid using the Electro-Magnetic Transient Program (EMTP). The test results validated the algorithm’s ability in distinguishing between transient arcing and permanent faults and determining the instant of secondary arc extinction.展开更多
文摘An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packet theory to adaptive beamforming, a wavelet packet transform-based adaptive beamforming algorithm (WP-ABF) is proposed . This WP-ABF algorithm uses wavelet packet transform as the preprocessing, and the wavelet packet transformed signal uses least mean square algorithm to implement the ~adaptive beamforming. White noise can be wiped off under wavelet packet transform according to the different characteristics of signal and white under the wavelet packet transform. Theoretical analysis and simulations demonstrate that the proposed WP-ABF algorithm converges faster than the conventional adaptive beamforming algorithm and the wavelet transform-based beamforming algorithm. Simulation results also reveal that the convergence of the algorithm relates closely to the wavelet base and series; that is, the algorithm convergence gets better with the increasing of series, and for the same series of wavelet base the convergence gets better with the increasing of regularity.
文摘A new adaptive Packet algorithm based on Discrete Cosine harmonic wavelet transform (DCHWT), (DCAHWP) has been proposed. This is realized by the Discrete Cosine Harmonic Wavelet transform (DCHTWT) which exploits the good properties of DCT viz., energy compaction (low leakage), frequency resolution and computational simplicity due its real nature, compared to those of DFT and its harmonic wavelet version. Hence the proposed wavelet packet is advantageous both in terms of performance and computational efficiency compared to those of existing DFT harmonic wavelet packet. Further, the new DCAHWP also enjoys the desirable properties of a Harmonic wavelet transform over the time domain WT, viz., built in decimation without any explicit antialiasing filtering and easy interpolation by mere concatenation of different scales in frequency (DCT) domain with out any image rejection filter and with out laborious delay compensation required. Further, the compression by the proposed DCAHWP is much better compared to that by adaptive WP based on Daubechies-2 wavelet (DBAWP). For a compression factor (CF) of 1/8, the ratio of the percentage error energy by proposed DCAHWP to that by DBAWP is about 1/8 and 1/5 for considered 1-D signal and speech signal, respectively. Its compression performance is better than that of DCHWT, both for 1-D and 2-D signals. The improvement is more significant for signals with abrupt changes or images with rapid variations (textures). For compression factor of 1/8, the ratio of the percentage error energy by DCAHWP to that by DCHWT, is about 1/3 and 1/2, for the considered 1-D signal and speech signal, respectively. This factor for an image considered is 2/3 and in particular for a textural image it is 1/5.
基金Supported by the National High-Tech Research and Development (863) Program of China (No. 2007AA120408)
文摘A satellite image adaptive restoration method was developed that avoids ringing artifacts at the image boundary and retains oriented features. The method combines periodic plus smooth image decom- position with complex wavelet packet transforms. The framework first decomposes a degraded satellite im- age into the sum of a ＂periodic component＂ and a ＂smooth component＂. The Bayesian method is then used to estimate the modulation transfer function degradation parameters and the noise. The periodic component is deconvoluted using complex wavelet packet transforms with the deconvolution result of the periodic component then combined with the smooth component to get the final recovered result. Tests show that this strategy effectively avoids ringing artifacts while preserving local image details （especially directional tex- tures） without amplifying the noise. Quantitative comparisons illustrate that the results are comparable with previous methods. Another benefit is that this approach can process large satellite images with parallel processing, which is important for practical use.
基金Supported by the Tianjin Natural Science Foundation in China (No.043600611)the Science and Technique Fostering Foundation of Tianjin in China (No. 043102911)
文摘One of the major issues with multi-carrier systems is their vulnerability to timing synchronization errors resulting in the loss of time synchronization which causes loss of orientation of incoming data at the receiver. This paper presents an acquisition algorithm to timing recovery using the decision-aided extended Kalman filtering （EKF） technique for nonlinear disturbance channels in a wavelet packet transform-based multicarrier modulation communication system. This timing recovery algorithm gives faster convergence, smaller root mean square （RMS） errors, and better bit error rate （BER） performance than traditional timing recovery methods, such as the phase-locked loop （PLL）, maximum likelihood （ML）, and Kalman filter （KF） methods. Thus, the algorithm is able to handle larger timing errors more reliably and to provide better timing recovery, since the scheme takes into account the nonlinear relationship between the signal samples and timing errors. Simulations for various time-varying channels show that the timing recovery algorithm works well for wavelet packet transform-based multicarrier modulation communication systems.
文摘We present a new algorithm for adaptive single-pole auto-reclosing of power transmission lines using wavelet packet transform. The db8 wavelet packet decomposes the faulted phase voltage waveform to obtain the coefficients of the nodes 257, 259 to 262. An index is then defined from the sum of the energy coefficients of these nodes. By evaluating the index, transient and permanent faults, as well as the secondary arc extinction instant, can be identified. The significant advantage of the proposed algorithm is that it does not need a threshold level and therefore its performance is independent of fault location, line parameters, and operating conditions. Moreover, it can be used in transmission lines with reactor compensation. The proposed method has been successfully tested under a variety of fault conditions on a 400 kV overhead line of the Iranian National Grid using the Electro-Magnetic Transient Program (EMTP). The test results validated the algorithm’s ability in distinguishing between transient arcing and permanent faults and determining the instant of secondary arc extinction.
