The contourlet Transform is an efficient directional multiresolution image representation, but it is not shift-invariant. The nonsubsampled contourlet transform (NSCT), is a fully shift-invariant, multiscale, and mult...
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The contourlet Transform is an efficient directional multiresolution image representation, but it is not shift-invariant. The nonsubsampled contourlet transform (NSCT), is a fully shift-invariant, multiscale, and multidirection expansion that has a fast implementation, but the computational efficiency is lower than the contourlet transform, such an efficient representation has to be obtained by structured transform and fast algorithm. In this paper, we adopt an optimized directional filter bank and embed it into NSCT to pursue the desired speed, sacrificed the PSNR of the reconstructed image, we obtain the obvious increase of processing speed. Experimental results show that the quality of reconstructed image is sufficient for the human visual system (HVS), and the modified NSCT has a speed about several times than the speed of the customary one, this is very valuable for practical applications of the NSCT.
Traditional recurrent neural networks are composed of capacitors, inductors, resistors, and operational *** neural networks are constructed by replacing resistors with memristors. This paper focuses on the memory anal...
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Traditional recurrent neural networks are composed of capacitors, inductors, resistors, and operational *** neural networks are constructed by replacing resistors with memristors. This paper focuses on the memory analysis,i.e. the initial value computation, of memristors. Firstly, we present the memory analysis for a single memristor based on memristors’ mathematical models with linear and nonlinear ***, we present the memory analysis for two memristors in series and parallel. Thirdly, we point out the difference between traditional neural networks and those that are memristive. Based on the current and voltage relationship of memristors, we use mathematical analysis and SPICE simulations to demonstrate the validity of our methods.
An example based super-resolution algorithm for digital video using contourlet transform is proposed in this paper. The input is a low resolution video sequence together with a high resolution still image of similar c...
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An example based super-resolution algorithm for digital video using contourlet transform is proposed in this paper. The input is a low resolution video sequence together with a high resolution still image of similar content. Firstly, the low resolution frames are interpolated to the same spatial resolution as the reference still image. For the good properties of directional, multiscale and anisotropy, the nonsub-sampled contourlet is utilized to create the training set of transform coefficient patches from the high resolution still image. Block based motion estimation is then applied inside the complete training set to find the best matching between interpolated frame and reference still image. According to the correspondence between low frequency and high frequency pairs, the missing high frequency information of the input frame can be easily learned from the training set. Finally, an inverse contourlet transform is applied to the interpolated frame and supplement high frequency subbands to recover the super-resolved image. Preliminary experimental results on video frames show that the proposed super- resolution algorithm outperforms conventional spatial interpolation methods and wavelet based interpolation algorithm both in visual quality and the PSNR value.
In this paper, we provided an algorithm to reconstruct images with Least Squares Support Vector Machines (LS-SVM) and Simulated Annealing Particle Swarm Optimization (APSO), named SAP. This algorithm introduces simula...
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In this paper,accelerated saddle point dynamics is proposed for distributed resource allocation over a multi-agent network,which enables a hyper-exponential convergence ***,an inertial fast-slow dynamical system with ...
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In this paper,accelerated saddle point dynamics is proposed for distributed resource allocation over a multi-agent network,which enables a hyper-exponential convergence ***,an inertial fast-slow dynamical system with vanishing damping is introduced,based on which the distributed saddle point algorithm is *** dual variables are updated in two time scales,i.e.,the fast manifold and the slow *** the fast manifold,the consensus of the Lagrangian multipliers and the tracking of the constraints are pursued by the consensus *** the slow manifold,the updating of the Lagrangian multipliers is accelerated by inertial ***-exponential stability is defined to characterize a faster convergence of our proposed algorithm in comparison with conventional primal-dual algorithms for distributed resource *** simulation of the application in the energy dispatch problem verifies the result,which demonstrates the fast convergence of the proposed saddle point dynamics.
Re-entry aircraft depends on aerodynamic force during flight. Because of windward rudder and lee rudder, there certainly exists aerodynamic coupling among pitch channel, yaw channel and roll channel under the situatio...
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In this paper, we proposed a susceptible-infected model with variant infection rates because different individuals have different resistance to diseases in different periods of real epidemic events. We consider two ca...
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Based on the current development of Model Driven Architecture (MDA) in Enterprise Information System (EIS), the paper proposes a DMDA, a new development architecture to improve EIS development speed and quality. The b...
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Electric power, potable water, telecommunications, natural gas, and transportation are examples of critical infrastructures, the intrinsic feature of which are suitable for network analysis. This paper proposes a meth...
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With a concern about the missile attitude control system, this paper attempts to solve the online calculation method of the coefficient of the small deviation equation, on which a LFT-based LPV model of the missile at...
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