The cooperative transmission schemes based on the amplify and forward(AF) mode have the defect of low transmission rate and the exiting full-rate cooperative transmission schemes based on space-time code design have...
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ISBN:
(纸本)9781467349994
The cooperative transmission schemes based on the amplify and forward(AF) mode have the defect of low transmission rate and the exiting full-rate cooperative transmission schemes based on space-time code design have the defect of high detection ***,this paper makes the best of linear constellation precoding(LCP) technique and cyclic delay diversity(CDD) technique,and adopts the nonorthogonal amplify and forward(NAF) mode,finally proposes a new full-rate wireless cooperative transmission scheme based on space-time-frequency code *** with the cooperative transmission schemes that only pursue the transmission rate or the BER performance,this new scheme can apply to multi-relay scenario,and has the advantages of simple structure,low signal detection complexity that does not increases with the number of relay *** of above makes the real-time data transmission service of high quality come to be possible.
A multi-residual module stacked hourglass network(MRSH)was proposed to improve the accuracy and robustness of human body pose *** network uses multiple hourglass sub-networks and three new residual *** the hourglass s...
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A multi-residual module stacked hourglass network(MRSH)was proposed to improve the accuracy and robustness of human body pose *** network uses multiple hourglass sub-networks and three new residual *** the hourglass sub-network,the large receptive field residual module(LRFRM)and the multi-scale residual module(MSRM)are first used to learn the spatial relationship between features and body parts at various *** the improved residual module(IRM)is used when the resolution is *** final network uses four stacked hourglass sub-networks,with intermediate supervision at the end of each hourglass,repeating high-low(from high resolution to low resolution)and low-high(from low resolution to high resolution)*** network was tested on the public datasets of Leeds sports poses(LSP)and MPII human *** experimental results show that the proposed network has better performance in human pose estimation.
The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this *** the conventional...
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The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this *** the conventional MLCBFM based on Foldy-Lax multiple scattering equations,the improvement is only made in the generation of characteristic basis functions(CBFs).However,it does not provide a change in impedance matrix filling and reducing matrix calculation procedure,which is *** reality,all the impedance and reduced matrix of each level of the MLCBFM have low-rank property and can be calculated ***,ACA is used for the efficient generation of two-level CBFs and the fast calculation of reduced matrix in this *** results are given to demonstrate the accuracy and efficiency of the method.
We study trace codes with defining set L,a subgroup of the multiplicative group of an extension of degree m of a certain ring of order 27. These codes are abelian, and their ternary images are quasi-cyclic of coindex ...
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We study trace codes with defining set L,a subgroup of the multiplicative group of an extension of degree m of a certain ring of order 27. These codes are abelian, and their ternary images are quasi-cyclic of coindex three(a.k.a. cubic codes). Their Lee weight distributions are computed by using Gauss sums. These codes have three nonzero weights when m is singly-even. When m is odd, under some hypothesises on the size of L, we obtain two new infinite families of two-weight codes which are optimal. Applications of the image codes to secret sharing schemes are also given.
In tile process of the reconstruction of digital holography. the traditional methods of diffraction and filtration are commonly adopted to recover the original complex-wave signal. Influenced by twin-image and zero-or...
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In tile process of the reconstruction of digital holography. the traditional methods of diffraction and filtration are commonly adopted to recover the original complex-wave signal. Influenced by twin-image and zero-order terms, the above-mentioned methods, however, either limit tile field of vision or result in the loss of the amplitude and phase. A new method for complex-wave retrieval is presented, which is based on blind signal separation. Three frames of holograms are captured by a charge coupled device (CCD) camera to form an observation signal. The term containing only amplitude and phase of complex-wave is separated, by means of independent component analysis, from the observation signal, which effectively eliminates the zero-order term. Finally. the complex-wave retrieval of pure phase wavefront is achieved. Experimental results show that this method can better recover the amplitude and phase of the original complex-wave even when there is a frequency spectrum mixture in the hologram.
In our study, support vector value contourlet transform is constructed by using support vector regression model and directional filter banks. The transform is then used to decompose source images at multi-scale, multi...
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In our study, support vector value contourlet transform is constructed by using support vector regression model and directional filter banks. The transform is then used to decompose source images at multi-scale, multi-direction and multi-resolution. After that, the super-resolved multi-spectral image is reconstructed by utilizing the strong learning ability of support vector regression and the correlation between multi-spectral image and panchromatic image. Finally, the super-resolved multi- spectral image and the panchromatic image are fused based on regions at different levels. Our experi- ments show that, the learning method based on support vector regression can improve the effect of super-resolution of multi-spectral image. The fused image preserves both high space resolution and spectrum information of multi-spectral image.
In this paper, we focus on the Hopf bifurcation control of a small-world network model with time-delay. With emphasis on the relationship between the Hopf bifurcation and the time-delay, we investigate the effect of t...
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An efficient method for simulating electromagnetic scattering from a dielectric rough surface over a frequency band is proposed. The method is based on the Chebyshev series and the Maehly approximation. The tapered pl...
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Abstractive summarization has made significant progress in recent years, which aims to generate a concise and coherent summary that contains the most important facts from the source document. Current fine-tuning appro...
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Abstractive summarization has made significant progress in recent years, which aims to generate a concise and coherent summary that contains the most important facts from the source document. Current fine-tuning approaches based on pre-training models typically rely on autoregressive and maximum likelihood estimation, which may result in inconsistent historical distributions generated during the training and inference stages, i.e., exposure bias problem. To alleviate this problem, we propose a hybrid fine-tuning model(HyFit), which combines contrastive learning and reinforcement learning in a diverse sampling space. Firstly, we introduce reparameterization and probability-based sampling methods to generate a set of summary candidates called candidates bank, which improves the diversity and quality of the decoding sampling space and incorporates the potential for uncertainty. Secondly, hybrid fine-tuning with sampled candidates bank, upweighting confident summaries and downweighting unconfident ones. Experiments demonstrate that HyFit significantly outperforms the state-of-the-art models on SAMSum and DialogSum. HyFit also shows good performance on low-resource summarization, on DialogSum dataset, using only approximate 8% of the examples exceed the performance of the base model trained on all examples. IEEE
Compressed ghost imaging can effectively enhance the quality of original image from far fewer measurements,but due to the non-negativity of the measurement matrix,the recover quality is thus *** this paper,singular va...
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ISBN:
(数字)9781510630765
ISBN:
(纸本)9781510630758
Compressed ghost imaging can effectively enhance the quality of original image from far fewer measurements,but due to the non-negativity of the measurement matrix,the recover quality is thus *** this paper,singular value decomposition compressed ghost imaging is proposed;First,the singular value decomposition be used to decompose the measurement matrix,and then the optimized measurement matrix and measurements are used to recover the original *** experiments verify the superiority of our proposed singular value decomposition compression ghost imaging method.
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