We present a robust mesh sharpening approach to reconstructing sharp features from blended or chamfered features, even with noise and aliasing errors. Feature regions were first recognized via normal variation accordi...We present a robust mesh sharpening approach to reconstructing sharp features from blended or chamfered features, even with noise and aliasing errors. Feature regions were first recognized via normal variation according to the user's input, and then normal filtering was applied to faces of feature regions. Finally, the vertices of the feature region were gradually updated based on new face normals using a least-squares error criterion. Experimental results demonstrate that the method is effective and robust in sharpening meshes.展开更多
The most challenging problem in mesh denoising is to distinguish features from noise. Based on the robust guided normal estimation and alternate vertex updating strategy, we investigate a new feature-preserving mesh d...The most challenging problem in mesh denoising is to distinguish features from noise. Based on the robust guided normal estimation and alternate vertex updating strategy, we investigate a new feature-preserving mesh denoising method. To accurately capture local structures around features, we propose a corner-aware neighborhood （CAN） scheme. By combining both overall normal distribution of all faces in a CAN and individual normal influence of the interested face, wc give a new consistency measuring method, which greatly improves the reliability of the estimated guided normals. As the noise level lowers, we take as guidance the previous filtered normals, which coincides with the emerging roUing guidance idea. In the vertex updating process, we classify vertices according to filtered normals at each iteration and reposition vertices of distinct types alternately with individual regularization constraints. Experiments on a variety of synthetic and real data indicate that our method adapts to various noise, both Gaussian and impulsive, no matter in the normal direction or in a random direction, with fcw triangles flippcd.展开更多
The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorit...The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.展开更多
A new normalized least mean square(NLMS) adaptive filter is first derived from a cost function, which incorporates the conventional one of the NLMS with a minimum-disturbance(MD)constraint. A variable regularization f...A new normalized least mean square(NLMS) adaptive filter is first derived from a cost function, which incorporates the conventional one of the NLMS with a minimum-disturbance(MD)constraint. A variable regularization factor(RF) is then employed to control the contribution made by the MD constraint in the cost function. Analysis results show that the RF can be taken as a combination of the step size and regularization parameter in the conventional NLMS. This implies that these parameters can be jointly controlled by simply tuning the RF as the proposed algorithm does. It also demonstrates that the RF can accelerate the convergence rate of the proposed algorithm and its optimal value can be obtained by minimizing the squared noise-free posteriori error. A method for automatically determining the value of the RF is also presented, which is free of any prior knowledge of the noise. While simulation results verify the analytical ones, it is also illustrated that the performance of the proposed algorithm is superior to the state-of-art ones in both the steady-state misalignment and the convergence rate. A novel algorithm is proposed to solve some problems. Simulation results show the effectiveness of the proposed algorithm.展开更多
Here some properties on filters of double MS-algebras are descripted. We show that,for a normal filter F of a double MS-algebra (L;0, + )(x,y) ∈θ(F) (a,b ∈ F) (x ∧α)∨b+= (y ∧ a)∨ b+.
This article deals with two important issues in digital filter implementation： roundoff noise and limit cycles. A novel class of robust state-space realizations, called normal realizations, is derived and characteriz...This article deals with two important issues in digital filter implementation： roundoff noise and limit cycles. A novel class of robust state-space realizations, called normal realizations, is derived and characterized. It is seen that these realizations are free of limit cycles. Another interesting property of the normal realizations is that they yield a minimal error propagation gain. The optimal realization problem, defined as to find those normal realizations that minimize roundoff noise gain, is formulated and solved analytically. A design example is presented to demonstrate the behavior of the optimal normal realizations and to compare them with several well-known digital filter realizations in terms of minimizing the roundoff noise and the error propagation.展开更多
The wash-out filter （WF） technique is used to control the flutter of a two dimensional airfoil with cubic non-linearity in incompressible flow. Firstly, Hopf bifurcation theory is used to determine the point at whic...The wash-out filter （WF） technique is used to control the flutter of a two dimensional airfoil with cubic non-linearity in incompressible flow. Firstly, Hopf bifurcation theory is used to determine the point at which the nonlinear controller is introduced. The system is then transformed into Jordan canonical form, based on analysis of linearized eigenvalues of the system. Secondly, for the introduced WF controller, the linear control gain is determined according to Hopf bifurcation condition. The sym- bolic computing program of normal form direct method （NFDM） is also used to obtain the normal form of the controlled system. The non-linear control gain can be determined based on the relation of the type of bifurcation and the parameters of the normal form, to transform sub-critical Hopf bifurcation to be su- per-critical one. Lastly, numerical simulations are used to certify the validity of theoretical analysis, in which the amplitude of flutter or limit cycle of the controlled system is reduced greatly, comparing to the original system.展开更多
Building detection in very high resolution (VHR) remote sensing images is crucial for many urban planning and management applications. Since buildings are elevated objects, the incorporation of elevation data provides...Building detection in very high resolution (VHR) remote sensing images is crucial for many urban planning and management applications. Since buildings are elevated objects, the incorporation of elevation data provides a mean to reliable detection. However, almost all existing methods of elevation-based building detection must first generate a normalized Digital Surface Model (nDSM). This model is generated by processes of extracting and subtracting terrain elevations from the DSM data. The generation of accurate nDSM is still a challenging task to some extent. This paper introduces a segment-based terrain filtering (SegTF) technique to filter out the terrain elevations directly using DSM elevations. This technique has four steps: elevation co-registration, image segmentation, slope calculation, and building detection. These steps of the developed technique were applied to a dataset that consisted of a VHR image and a corresponding DSM for detecting buildings. The result of the building detection was evaluated and found to be 100% correct with an overall detection quality of 93%. These values indicate a highly reliable and promising technique for mapping buildings in VHR images.展开更多
A novel adaptive algorithm of IIR lattice notch filter realized by all-pass filter is presented. The time-averaged estimation of cross correlation of the present instantaneous input signal and the past output signal i...A novel adaptive algorithm of IIR lattice notch filter realized by all-pass filter is presented. The time-averaged estimation of cross correlation of the present instantaneous input signal and the past output signal is used to update the step-size, leading to a considerably improved convergence rate in a low SNR situation and reduced steady-state bias and MSE. The theoretical expression for steady-state bounds on the step-size is derived, and the influence factors on the stable performance of the algorithm theoretically are analyzed. A normalized power factor is then introduced to control variation of step-size in its steady-state bounds. This technique prevents divergence due to the influence of large power input signal and improves robustness. Numerical experiments are performed to demonstrate superiority of the proposed method.展开更多
By means of a characterization of compact spaces in terms of open CD*-filters induced by a , a - and open CD*-filters process of compactifications of an arbitrary topological space Y is obtained in Sec. 3 by embedding...By means of a characterization of compact spaces in terms of open CD*-filters induced by a , a - and open CD*-filters process of compactifications of an arbitrary topological space Y is obtained in Sec. 3 by embedding Y as a dense subspace of , YS = {ε |ε is an open CD*-filter that does not converge in Y}, YT = {A|A is a basic open CD*-filter that does not converge in Y}, is the topology induced by the base B = {U*|U is open in Y, U ≠φ} and U* = {F∈Ysw (or YTw)|U∈F}. Furthermore, an arbitrary Hausdorff compactification (Z, h) of a Tychonoff space X?can be obtained from a by the?similar process in Sec.3.展开更多
基金supported by the Hi-Tech Research and Development Pro-gram (863) of China (Nos. 2007AA01Z311 and 2007AA04Z1A5)the Doctoral Fund of MOE of China (No. 20060335114)the Science and Technology Program of Zhejiang Province, China (No. 2007C21006)
文摘We present a robust mesh sharpening approach to reconstructing sharp features from blended or chamfered features, even with noise and aliasing errors. Feature regions were first recognized via normal variation according to the user's input, and then normal filtering was applied to faces of feature regions. Finally, the vertices of the feature region were gradually updated based on new face normals using a least-squares error criterion. Experimental results demonstrate that the method is effective and robust in sharpening meshes.
基金Project supported by the National Natural Science Foundation of China （Nos. 61402224 and 61222206）, the Natural Science Foundation of Jiangsu Province, China （No. BK2014833）, and the Natural Science Foundation of Suzhou University of Science and Technology, China （No. XKZ201611）.Acknowledgements The authors would like to appreciate Wang-yu ZHANG for providing executable programs. The models used in this paper are courtesy of the AIM Shape Repos- itory, the Stanford 3D Scanning Repository, and Laser Design.
文摘The most challenging problem in mesh denoising is to distinguish features from noise. Based on the robust guided normal estimation and alternate vertex updating strategy, we investigate a new feature-preserving mesh denoising method. To accurately capture local structures around features, we propose a corner-aware neighborhood （CAN） scheme. By combining both overall normal distribution of all faces in a CAN and individual normal influence of the interested face, wc give a new consistency measuring method, which greatly improves the reliability of the estimated guided normals. As the noise level lowers, we take as guidance the previous filtered normals, which coincides with the emerging roUing guidance idea. In the vertex updating process, we classify vertices according to filtered normals at each iteration and reposition vertices of distinct types alternately with individual regularization constraints. Experiments on a variety of synthetic and real data indicate that our method adapts to various noise, both Gaussian and impulsive, no matter in the normal direction or in a random direction, with fcw triangles flippcd.
基金Project(50905037) supported by the National Natural Science Foundation of ChinaProject(20092304120014) supported by Specialized Research Fund for the Doctoral Program of Higher Education of China+2 种基金 Project(20100471021) supported by the China Postdoctoral Science Foundation Project(LBH-Q09134) supported by Heilongjiang Postdoctoral Science-Research Foundation,China Project (HEUFT09013) supported by the Foundation of Harbin Engineering University,China
文摘The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.
基金supported by the National Natural Science Foundation of China(61571131 11604055)
文摘A new normalized least mean square(NLMS) adaptive filter is first derived from a cost function, which incorporates the conventional one of the NLMS with a minimum-disturbance(MD)constraint. A variable regularization factor(RF) is then employed to control the contribution made by the MD constraint in the cost function. Analysis results show that the RF can be taken as a combination of the step size and regularization parameter in the conventional NLMS. This implies that these parameters can be jointly controlled by simply tuning the RF as the proposed algorithm does. It also demonstrates that the RF can accelerate the convergence rate of the proposed algorithm and its optimal value can be obtained by minimizing the squared noise-free posteriori error. A method for automatically determining the value of the RF is also presented, which is free of any prior knowledge of the noise. While simulation results verify the analytical ones, it is also illustrated that the performance of the proposed algorithm is superior to the state-of-art ones in both the steady-state misalignment and the convergence rate. A novel algorithm is proposed to solve some problems. Simulation results show the effectiveness of the proposed algorithm.
文摘Here some properties on filters of double MS-algebras are descripted. We show that,for a normal filter F of a double MS-algebra (L;0, + )(x,y) ∈θ(F) (a,b ∈ F) (x ∧α)∨b+= (y ∧ a)∨ b+.
基金the National Nature Science Foundation of China (60774021)
文摘This article deals with two important issues in digital filter implementation： roundoff noise and limit cycles. A novel class of robust state-space realizations, called normal realizations, is derived and characterized. It is seen that these realizations are free of limit cycles. Another interesting property of the normal realizations is that they yield a minimal error propagation gain. The optimal realization problem, defined as to find those normal realizations that minimize roundoff noise gain, is formulated and solved analytically. A design example is presented to demonstrate the behavior of the optimal normal realizations and to compare them with several well-known digital filter realizations in terms of minimizing the roundoff noise and the error propagation.
文摘The wash-out filter （WF） technique is used to control the flutter of a two dimensional airfoil with cubic non-linearity in incompressible flow. Firstly, Hopf bifurcation theory is used to determine the point at which the nonlinear controller is introduced. The system is then transformed into Jordan canonical form, based on analysis of linearized eigenvalues of the system. Secondly, for the introduced WF controller, the linear control gain is determined according to Hopf bifurcation condition. The sym- bolic computing program of normal form direct method （NFDM） is also used to obtain the normal form of the controlled system. The non-linear control gain can be determined based on the relation of the type of bifurcation and the parameters of the normal form, to transform sub-critical Hopf bifurcation to be su- per-critical one. Lastly, numerical simulations are used to certify the validity of theoretical analysis, in which the amplitude of flutter or limit cycle of the controlled system is reduced greatly, comparing to the original system.
文摘Building detection in very high resolution (VHR) remote sensing images is crucial for many urban planning and management applications. Since buildings are elevated objects, the incorporation of elevation data provides a mean to reliable detection. However, almost all existing methods of elevation-based building detection must first generate a normalized Digital Surface Model (nDSM). This model is generated by processes of extracting and subtracting terrain elevations from the DSM data. The generation of accurate nDSM is still a challenging task to some extent. This paper introduces a segment-based terrain filtering (SegTF) technique to filter out the terrain elevations directly using DSM elevations. This technique has four steps: elevation co-registration, image segmentation, slope calculation, and building detection. These steps of the developed technique were applied to a dataset that consisted of a VHR image and a corresponding DSM for detecting buildings. The result of the building detection was evaluated and found to be 100% correct with an overall detection quality of 93%. These values indicate a highly reliable and promising technique for mapping buildings in VHR images.
文摘A novel adaptive algorithm of IIR lattice notch filter realized by all-pass filter is presented. The time-averaged estimation of cross correlation of the present instantaneous input signal and the past output signal is used to update the step-size, leading to a considerably improved convergence rate in a low SNR situation and reduced steady-state bias and MSE. The theoretical expression for steady-state bounds on the step-size is derived, and the influence factors on the stable performance of the algorithm theoretically are analyzed. A normalized power factor is then introduced to control variation of step-size in its steady-state bounds. This technique prevents divergence due to the influence of large power input signal and improves robustness. Numerical experiments are performed to demonstrate superiority of the proposed method.
文摘By means of a characterization of compact spaces in terms of open CD*-filters induced by a , a - and open CD*-filters process of compactifications of an arbitrary topological space Y is obtained in Sec. 3 by embedding Y as a dense subspace of , YS = {ε |ε is an open CD*-filter that does not converge in Y}, YT = {A|A is a basic open CD*-filter that does not converge in Y}, is the topology induced by the base B = {U*|U is open in Y, U ≠φ} and U* = {F∈Ysw (or YTw)|U∈F}. Furthermore, an arbitrary Hausdorff compactification (Z, h) of a Tychonoff space X?can be obtained from a by the?similar process in Sec.3.
