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检索条件"主题词=iterative algorithm"

共 1765 条记录，以下是1341-1350 订阅

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The Novel iterative Interference Alignment Scheme for the SISO Interference Channel

The Novel Iterative Interference Alignment Scheme for the SI...

引用

2010 IEEE 71st Vehicular Technology Conference

作者： Shen, Hui Li, Bin Huawei Technol Dept Wireless Res Shenzhen Peoples R China

ISBN: (纸本)9781424425198

In this paper, we propose a novel iterative interference alignment (IA) scheme for the single-input single-output (SISO) interference channel system using minimum total mean square error criterion under the individual transmitter power constraints. We show that interference alignment under such criterion could be realized through an iterative algorithm. The convergence of the proposed algorithm is discussed. Simulation results, compared with several existing IA schemes, show that the proposed scheme can effectively improve the BER performance of the SISO interference channel system while maintaining the same degree of freedom as Cadambe-Jafar scheme.

关键词： SISO interference channel interference alignment iterative algorithm

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Improvement of SPGD by Gradient Descent Optimization algorithm in Deep Learning

Improvement of SPGD by Gradient Descent Optimization Algorit...

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Asia Communications and Photonics Conference (ACP) / International Conference on Information Photonics and Optical Communications (IPOC)

作者： Zhao, Qingsong Hao, Shiqi Wang, Yong Wang, Lei Lin, Zhi Natl Univ Def Technol AnHui Prov Key Lab Elect Restrict Coll Elect Countermeasure Hefei Peoples R China

ISBN: (纸本)9781665481557

The distortion caused by atmospheric turbulence can be compensated by wavefront correction, which improves the performance of free space optical vortex beam communication. In order to solve the slow convergence problem of the traditional stochastic parallel gradient descent algorithm in wavefront correction, an iterative correction algorithm based on adaptive gain factor is presented, which is combined with the Adam optimization algorithm in deep learning. The simulation verifies that the algorithm is more robust in turbulent environment.

关键词： wavefront correction iterative algorithm atmospheric turbulence

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Cooperative Network Localizability via Semidefinite Programming

Cooperative Network Localizability via Semidefinite Programm...

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22nd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Noureddine, Hadi Castelain, Damien Pyndiah, Ramesh Mitsubishi Electric R&D Centre Europe France

ISBN: (纸本)9781457713484

In cooperative localization, the aim is to compute the locations in Euclidean space of a set of nodes performing pair-wise distance measurements. In cases of lack of measurements, several nodes might have multiple feasible solutions meeting the distance constraints. In this paper, we are interested in identifying the nodes that have a unique solution. By employing a semidefinite programming (SDP) formulation of the problem, it is possible to identify only a portion of the uniquely solvable nodes. To improve the identification of these nodes, we develop an iterative algorithm based on SDP. At each iteration, the objective function of the SDP problem is modified in order to identify additional uniquely solvable nodes. We apply this algorithm to study the statistical occurrence of uniquely solvable nodes in uniformly generated networks, and compare the results with the simple SDP. We also investigate the errors in the computed locations for both methods and a variant of the SDP method augmented by bounding constraints on unobserved distances.

关键词： Euclidean space SDP method SDP problem cooperative communication cooperative localization cooperative network localizability distance constraint distance measurement iterative algorithm iterative methods mathematical programming multiple feasible solution pairwise distance measurement semidefinite programming statistical analysis statistical occurrence

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Fast Parallel Processing using GPU in computing L1-PCA bases

Fast Parallel Processing using GPU in computing L1-PCA bases

引用

IEEE Region 10 Conference on TENCON 2010

作者： Funatsu, Nobuhiro Kuroki, Yoshimitsu Kurume Natl Coll Technol Kurume Fukuoka 8308555 Japan

ISBN: (纸本)9781424468904

In data-analysis problems with a large number of dimensions, the principal component analysis based on L2-norm ( L2-PCA) is one of the most popular methods, but L2-PCA is sensitive to outliers. Unlike L2-PCA, PCA-L1 is robust to outliers because it utilizes the L1-norm, which is less sensitive to outliers;therefore, some studies have shown the superiority of PCA-L1 to L2-PCA [2][3]. However, PCA-L1 requires enormous computational cost to obtain the bases, because PCA-L1 employs an iterative algorithm, and initial bases are eigenvectors of autocorrelation matrix. The autocorrelation matrix in the PCA-L1 needs to be recalculated for the each basis besides. In previous works [3], the authors proposed a fast PCA-L1 algorithm providing identical bases in terms of theoretical approach, and decreased computational time roughly to a quarter. This paper attempts to accelerate the computation of the L1-PCA bases using GPU.

关键词： GPU L2-PCA L2-norm autocorrelation matrix eigenvectors computer graphic equipment coprocessors data analysis data analysis problem eigenvalues and eigenfunctions fast parallel processing iterative algorithm iterative methods matrix algebra parallel proces

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Low-dose photon counting CT reconstruction bias reduction with multi-energy alternating minimization algorithm 15

Low-dose photon counting CT reconstruction bias reduction wi...

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15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine

作者： Lu, Jingwei Zhang, Shuangyue Politte, David G. O'Sullivan, Joseph A. Washington Univ Dept Elect & Syst Engn 1 Brookings Dr St Louis MO 63130 USA Washington Univ Sch Med Elect Radiol Lab Mallinckrodt Inst Radiol St Louis MO 63110 USA

ISBN: (数字)9781510628380

ISBN: (纸本)9781510628380

Photon counting CT (PCCT) is an x-ray imaging technique that has undergone great development in the past decade. PCCT has the potential to improve dose efficiency and low-dose performance. In this paper, we propose a statistics-based iterative algorithm to perform a direct reconstruction of material-decomposed images. Compared with the conventional sinogram-based decomposition method which has degraded performance in low-dose scenarios, the multi-energy alternating minimization algorithm for photon counting CT (MEAM-PCCT) can generate accurate material-decomposed image with much smaller biases.

关键词： photon counting low-dose radiation iterative algorithm spectral x-ray CT alternating minimization

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Numerical Evaluations for Multiplicative Algebraic Reconstruction Technique

Numerical Evaluations for Multiplicative Algebraic Reconstru...

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Biomedical Imaging and Sensing Conference

作者： Aoyagi, Tomohiro Ohtsubo, Kouichi Toyo Univ Fac Informat Sci & Arts 2100 Kujirai Kawagoe Shi Saitama 3508585 Japan

ISBN: (数字)9781510647206

ISBN: (纸本)9781510647206;9781510647190

Image reconstruction can be formulated by the Fredholm equation of the first kind The method of projections onto convex sets (POCS) is an iterative algorithm for solving the equation. Multiplicative algebraic reconstruction techniques (MART) is one of POCS for solving a system of simultaneous equation. By discretizing the image reconstruction problem, we applied the MART to the problems and evaluate the image quality in computer simulations. We also investigated the normalized mean square error of reconstructed images with respect to the variations of the number of detectors and views, the relaxation parameters.

关键词： image reconstruction MART POCS iterative algorithm tomography

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Semi-Supervised Learning for MIMO Detection 14

Semi-Supervised Learning for MIMO Detection

引用

14th IEEE International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Ao, Peiyan Li, Runhua Sun, Rongchao Xue, Jiang Xi An Jiao Tong Univ Math & Stat Xian Peoples R China

ISBN: (纸本)9781665450850

The model-driven deep learning method has been verified to be effective for signal detection in the massive multi-input multi-output (MIMO) system. In previous work, this kind of methods need to be trained with numerous pilots in a supervised manner, which will occupy amount of spectrum resources. In addition, the abundant information in the symbols are not utilized in the training procedure. To solve this issue, Firstly in this paper, a new unsupervised deep learning (DL) network named Un-OAMPNet is proposed, which considers Mixture of Gaussian (MoG) noise model under a maximum a posterior (MAP) framework. Secondly, Un-OAMPNet is extended to the semi-supervised DL network (Semi-OAMPNet) with a few pilots to increase the detection performance. In Semi-OAMPNet, the loss function is combined with the mean square error (MSE) loss in the supervised manner and the MAP loss in the unsupervised manner. In this way, Semi-OAMPNet inherits the advantages of OAMP-Net2 and gains better detection performance with fewer pilots. Simulation results show that the Un-OAMPNet is effective without any pilots in the training procedure and proposed Semi-OAMPNet has better performance compared with other model-driven detectors.

关键词： Model-driven MIMO detection iterative algorithm noise model semi-supervised learning

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Some practices of irregular sampling

Some practices of irregular sampling

引用

Conference on Advanced Signal Processing algorithms, Architectures, and Implementations XI

作者： Begonia, M Li, SD San Francisco State Univ San Francisco CA 94132 USA

ISBN: (纸本)0819441880

Based on a frame theoretical formulation of irregular sampling, conditions on sampling points are derived. Our formulation and sampling conditions are applicable to all subspaces (e.g. shift invariant, Gabor, bandlimited and bandpass subspaces). A focus is paid to the implementation of the algorithm in general. The method starts from constructing a pair of frames for a selected subspace, with which a sequence of sampling functions is fabricated based on a set of given irregular sampling points. The (irregular) sampling reconstruction is implemented through a frame-based iterative algorithm, which is guaranteed to converge. A Matlab package with a graphic user interface will be provided for users to view demos as well as try their own sampling reconstruction problems. Users are also allowed to construct their own subspaces. Parameters, sampling points and signals may all be entered by users. The program will automatically check for the fulfillment of the sampling conditions and provide a reconstruction of the signal. We believe that this is a useful tool for studies and practices of irregular samplings.

关键词： irregular sampling frame iterative algorithm reconstruction convergence subspace

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FRIM:: Minimum-variance reconstructor with a FRactal iterative Method

FRIM:: Minimum-variance reconstructor with a FRactal Iterati...

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Conference on Advances in Adaptive Optics II

作者： Bechet, Clementine Tallon, Michel Thiebaut, Eric UCBL ENS Lyon CRAL UMR5574 CNRS 9 Ave Charles Andre F-69531 St Genis Laval France

ISBN: (纸本)081946337X

Adaptive optics (AO) systems under study for the future generation of telescopes have to cope with a huge number of degrees of freedom. This number N is typically 2 orders of magnitude larger than for the currently existing AO systems. An iterative method using a fractal preconditioning, has recently been suggested for a minimum-variance reconstruction in O(N) operations. We analyze the efficiency of this algorithm for both the open-loop and the closed-loop configurations. We present the formalism and illustrate the assets of this method with simulations. While the number of iterations for convergence is around 10 in open-loop, the closed-loop configuration induces a reduction of the required number of iterations by a factor of 3 typically. This analysis also enhances the importance of introducing priors to ensure an optimal command. Closed-loop simulations demonstrate the loss of performance when no temporal priors are used. Besides, we discuss the importance of an accurate model for both the system and its uncertainties, so as to ensure a stable behavior in closed-loop.

关键词： adaptive optics control iterative algorithm preconditioning Extremely Large Telescopes

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iterative Constrained Weighted Least Squares Solution for Target Localization in Distributed MIMO Radar 27

Iterative Constrained Weighted Least Squares Solution for Ta...

引用

27th Iranian Conference on Electrical Engineering (ICEE)

作者： Noroozi, Ali Nayebi, Mohammad Mahdi Amiri, Rouhollah Sharif Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781728115085

This paper concentrates on the target localization problem in a distributed multiple-input multiple-output radar system using the bistatic range (BR) measurements. By linearizing the BR measurements and considering the relationship between the nuisance parameter and the target position, a constrained weighted least squares (CWLS) problem is formulated, which is an indefinite quadratically constrained quadratic programming problem. Since the constraint is non-convex, it is a nontrivial task to find the global solution. For this purpose, an improved Newton's method is applied to the CWLS problem to estimate the target position. Numerical simulations are included to examine the algorithm's performance and corroborate the theoretical developments.

关键词： Bistatic range (BR) constrained weighted least squares (CWLS) iterative algorithm target position

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