An isothermal compressive experiment using Gleeble 1500 thermal simulator was studied to acquire flow stress at different deformation temperatures, strains and strain rates. The artificial neural networks with the err...An isothermal compressive experiment using Gleeble 1500 thermal simulator was studied to acquire flow stress at different deformation temperatures, strains and strain rates. The artificial neural networks with the error back propagation(BP) algorithm was used to establish constitutive model of 2519 aluminum alloy based on the experiment data. The model results show that the systematical error is small(δ=3.3%) when the value of objective function is 0.2, the number of nodes in the hidden layer is 5 and the learning rate is 0.1. Flow stresses of the material under various thermodynamic conditions are predicted by the neural network model, and the predicted results correspond with the experimental results. A knowledge-based constitutive relation model is developed.展开更多
Inverse synthetic aperture radar(ISAR)imaging of near-field targets is potentially useful in some specific applications,which makes it very important to efficiently produce highquality image of the near-field target.I...Inverse synthetic aperture radar(ISAR)imaging of near-field targets is potentially useful in some specific applications,which makes it very important to efficiently produce highquality image of the near-field target.In this paper,the simplified target model with uniform linear motion is applied to the near-field target imaging,which overcomes the complexity of the traditional near-field imaging algorithm.According to this signal model,the method based on coordinate conversion and image interpolation combined with the range-Doppler(R-D)algorithm is proposed to correct the near-field distortion problem.Compared with the back-projection(BP)algorithm,the proposed method produces better focused ISAR images of the near-field target,and decreases the computation complexity significantly.Experimental results of the simulated data have demonstrated the effectiveness and robustness of the proposed method.展开更多
A new method of super-resolution image reconstruction is proposed, which uses a three-step-training error backpropagation neural network （BPNN） to realize the super-resolution reconstruction （SRR） of satellite ima...A new method of super-resolution image reconstruction is proposed, which uses a three-step-training error backpropagation neural network （BPNN） to realize the super-resolution reconstruction （SRR） of satellite image. The method is based on BPNN. First, three groups learning samples with different resolutions are obtained according to image observation model, and then vector mappings are respectively used to those three group learning samples to speed up the convergence of BPNN, at last, three times consecutive training are carried on the BPNN. Training samples used in each step are of higher resolution than those used in the previous steps, so the increasing weights store a great amount of information for SRR, and network performance and generalization ability are improved greatly. Simulation and generalization tests are carried on the well-trained three-step-training NN respectively, and the reconstruction results with higher resolution images verify the effectiveness and validity of this method.展开更多
Because the conventional ultra wideband（UWB） radar imaging algorithm cannot meet the demand in the capability of multiple targets detection,a novel UWB radar imaging algorithm based on the near field radiation theor...Because the conventional ultra wideband（UWB） radar imaging algorithm cannot meet the demand in the capability of multiple targets detection,a novel UWB radar imaging algorithm based on the near field radiation theory of dipole is presented.On the foundation of researching the principle of a time domain imaging algorithm,the back projection（BP） algorithm is derived and analyzed.Firstly,the far field sampling data are transferred to the near field sampling data by using the near field radiation theory of dipole.Then the BP algorithm is applied to target detection.The capability of the new algorithm to detect the multi-target is verified by using the finite-difference time-domain method,and the threedimensional images of targets are obtained.The coupling effect between targets for imaging is analyzed.The simulation results show that the new UWB radar imaging algorithm based on the near field radiation theory of dipole could weaken the coupling effect for imaging,and as a result the quality of imaging is improved.展开更多
文摘An isothermal compressive experiment using Gleeble 1500 thermal simulator was studied to acquire flow stress at different deformation temperatures, strains and strain rates. The artificial neural networks with the error back propagation(BP) algorithm was used to establish constitutive model of 2519 aluminum alloy based on the experiment data. The model results show that the systematical error is small(δ=3.3%) when the value of objective function is 0.2, the number of nodes in the hidden layer is 5 and the learning rate is 0.1. Flow stresses of the material under various thermodynamic conditions are predicted by the neural network model, and the predicted results correspond with the experimental results. A knowledge-based constitutive relation model is developed.
基金supported by the National Natural Science Foundation of China(61871146).
文摘Inverse synthetic aperture radar(ISAR)imaging of near-field targets is potentially useful in some specific applications,which makes it very important to efficiently produce highquality image of the near-field target.In this paper,the simplified target model with uniform linear motion is applied to the near-field target imaging,which overcomes the complexity of the traditional near-field imaging algorithm.According to this signal model,the method based on coordinate conversion and image interpolation combined with the range-Doppler(R-D)algorithm is proposed to correct the near-field distortion problem.Compared with the back-projection(BP)algorithm,the proposed method produces better focused ISAR images of the near-field target,and decreases the computation complexity significantly.Experimental results of the simulated data have demonstrated the effectiveness and robustness of the proposed method.
文摘A new method of super-resolution image reconstruction is proposed, which uses a three-step-training error backpropagation neural network （BPNN） to realize the super-resolution reconstruction （SRR） of satellite image. The method is based on BPNN. First, three groups learning samples with different resolutions are obtained according to image observation model, and then vector mappings are respectively used to those three group learning samples to speed up the convergence of BPNN, at last, three times consecutive training are carried on the BPNN. Training samples used in each step are of higher resolution than those used in the previous steps, so the increasing weights store a great amount of information for SRR, and network performance and generalization ability are improved greatly. Simulation and generalization tests are carried on the well-trained three-step-training NN respectively, and the reconstruction results with higher resolution images verify the effectiveness and validity of this method.
基金supported by the Key Laboratory of Millimeter Waves of China (K200907)
文摘Because the conventional ultra wideband（UWB） radar imaging algorithm cannot meet the demand in the capability of multiple targets detection,a novel UWB radar imaging algorithm based on the near field radiation theory of dipole is presented.On the foundation of researching the principle of a time domain imaging algorithm,the back projection（BP） algorithm is derived and analyzed.Firstly,the far field sampling data are transferred to the near field sampling data by using the near field radiation theory of dipole.Then the BP algorithm is applied to target detection.The capability of the new algorithm to detect the multi-target is verified by using the finite-difference time-domain method,and the threedimensional images of targets are obtained.The coupling effect between targets for imaging is analyzed.The simulation results show that the new UWB radar imaging algorithm based on the near field radiation theory of dipole could weaken the coupling effect for imaging,and as a result the quality of imaging is improved.
