Blind separation algorithm of PCMA signals with different symbol rates based on DG-PSP by Yi-ming GUO, Hua PENG, Yong YANG, Xue-juan WEI, Hao WANG

“…A blind separation algorithm was proposed for PCMA signals with different symbol rates based on double grid per-survivor processing (DG-PSP).The channel states and two input signal components were treated as two dynamic grids,receiving mixed-signal reconstructed by respectively iterative updating the two groups of grid status,thus achieving blind signal separation.The joint iterative decoding separation structure was focused,and a detailed analysis and comparison under different error estimation of parameters was shown.The complexity of the algorithm is similar to the traditional PSP algorithm.Simulation results show that,a gain of about 2 dB in signal-noise ratio can be obtained after the first iteration at a bit error rate of 10⁻²,and a gain of nearly 3 dB in signal-noise ratio can be obtained after the second iteration.…”
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Fault Diagnosis of Fan Bearings Based on an Improved Grey Wolf Optimization Algorithm and SVM by Liu Jinyan, Abulizi Maimaitireyimu, Xiang Zhicheng, Xie Lirong

Subjects: “…Improved grey wolf optimization algorithm…”
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Weakly supervised semantic segmentation and optimization algorithm based on multi-scale feature model by Changzhen XIONG, Hui ZHI

“…In order to improve the accuracy of weakly-supervised semantic segmentation method,a segmentation and optimization algorithm that combines multi-scale feature was proposed.The new algorithm firstly constructs a multi-scale feature model based on transfer learning algorithm.In addition,a new classifier was introduced for category prediction to reduce the failure of segmentation due to the prediction of target class information errors.Then the designed multi-scale model was fused with the original transfer learning model by different weights to enhance the generalization performance of the model.Finally,the predictions class credibility was added to adjust the credibility of the corresponding class of pixels in the segmentation map,avoiding false positive segmentation regions.The proposed algorithm was tested on the challenging VOC 2012 dataset,the mean intersection-over-union is 58.8% on validation dataset and 57.5% on test dataset.It outperforms the original transfer-learning algorithm by 12.9% and 12.3%.And it performs favorably against other segmentation methods using weakly-supervised information based on category labels as well.…”
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An Improved MPPT Algorithm for PV Generation Applications Based on P-U Curve Reconstitution by Yaoqiang Wang, Meiling Zhang, Xian Cheng

“…Therefore, a maximum power point (MPP) tracking (MPPT) algorithm is essential for the photovoltaic generation system. …”
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Combined Mechanism and Its Kinematics Inverse Algorithm for Realizing Constant Speed Reciprocating Motion by Yu Chen, Zhixian He, Peicheng Shi

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The Coral Reefs Optimization Algorithm: A Novel Metaheuristic for Efficiently Solving Optimization Problems by S. Salcedo-Sanz, J. Del Ser, I. Landa-Torres, S. Gil-López, J. A. Portilla-Figueras

“…This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. …”
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Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs by Thiago Fellipe Ortiz de Camargo, Thiago Fellipe Ortiz de Camargo, Guilherme Alberto Sousa Ribeiro, Guilherme Alberto Sousa Ribeiro, Maria Carolina Bueno da Silva, Luan Oliveira da Silva, Pedro Paulo Teixeira e Silva Torres, Denise do Socorro Rodrigues da Silva, Mayler Olombrada Nunes de Santos, William Salibe Filho, Marcela Emer Egypto Rosa, Magdala de Araujo Novaes, Thiago Augusto Massarutto, Osvaldo Landi Junior, Elaine Yanata, Marcio Rodrigues da Cunha Reis, Gilberto Szarf, Pedro Vieira Santana Netto, Joselisa Peres Queiroz de Paiva

“…The algorithm's performance was measured using accuracy, sensitivity, and specificity. …”
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A Nonmonotone Weighting Self-Adaptive Trust Region Algorithm for Unconstrained Nonconvex Optimization by Yunlong Lu, Weiwei Yang, Wenyu Li, Xiaowei Jiang, Yueting Yang

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Sparsity adaptive channel estimation algorithm based on compressive sensing for massive MIMO systems by Li-jun GE, Hui GUO, Yue LI, Lan ZHAO

“…A sparsity-adaptive channel estimation algorithm based on compressive sensing was proposed for massive MIMO systems when the number of channel multi-paths was unknown.By exploiting the joint sparsity characteristics of the sub-channels，the proposed block sparsity adaptive matching pursuit (BSAMP) algorithm first selected atoms by setting a threshold and finding the position of the maximum backward difference，which reduces the energy dispersion caused by the non-orthogonality of the observation matrix and improves the performance of the algorithm.Then a regularization method was utilized to improve the stability of the algorithm.Simulation results demonstrate that the proposed algorithm recovers the channel state information accurately and shows a high computational efficiency.…”
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Fair and efficient network congestion control algorithm based on minority game with local information by Zu-xi WANG, Zhao-zhang DENG, Li LI

“…Low link utility,RTT unfairness and unfairness of Multi-Bottleneck network are the existing problems in the present network congestion control algorithms at large.Considering the local information of network,a congestion control model based on minority game (MG) with local information was proposed to solve these problems.Based on the model,a congestion control algorithm was designed.The result of simulation indicates that the proposed algorithm has good performance on link utilization and fairness of RTT flow in multi-bottleneck network.…”
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Source-free domain transfer algorithm with reduced style sensitivity for medical image segmentation. by Jian Lin, Xiaomin Yu, Zhengxian Wang, Chaoqiong Ma

“…In unsupervised transfer learning for medical image segmentation, where existing algorithms face the challenge of error propagation due to inaccessible source domain data. …”
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An Efficient Laguerre-Based FDTD Iterative Algorithm in 3D Cylindrical Coordinate System by Da-Wei Zhu, Hai-Lin Chen, Zi-Yu Pan, Bo-Ao Xu, Bin Chen

“…Here an efficient Laguerre-based finite-difference time-domain iterative algorithm is proposed. Different from the previously developed iterative procedure used in the efficient FDTD algorithm, a new perturbation term combined with the Gauss–Seidel iterative procedure is introduced to form the new Laguerre-based FDTD algorithm in the 3D cylindrical coordinate system. …”
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Online Real-Time Trajectory Analysis Based on Adaptive Time Interval Clustering Algorithm by Jianjiang Li, Huihui Jiao, Jie Wang, Zhiguo Liu, Jie Wu

“…Experimental results show that the DAC-Stream algorithm improves the clustering effect and accelerates data processing compared with the fixed-time-interval clustering algorithm based on density grid (called DC-Stream).…”
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Preprocessing optimization algorithm based on partial channel information feedback in wideband OFDM systems by WANG Xia1, ZHANG Guo-mei1, XUE Tao2

“…To mitigate inter-block interference（IBI） and inter-carrier interference（ICI） in an orthogonal frequency divi-sion multiplexing（OFDM） system,pre-processing approaches at transmitters based on full channel state information（CSI） had been proposed,the performance improved and receiver simplied.However,feeding full CSI back would oc-cupy scarce bandwidth and was impractical sometimes for the systems with high real-time demand.To deal with this problem,a preprocessing optimization based on partial CSI feedback was investigated and three selected preprocessing approaches of optimization matrix were developed and tested.Computer simulation results showed that the proposed op-timization algorithm can effectively cancel IBI and ICI and significantly improve the performance in wideband OFDM systems.Compared with the pre-processing approaches at transmitters based on full CSI,under the condition of meeting the demand for quality of services（QoS）,the proposed scheme has high spectral efficiency and low feedback and com-putation complexity.…”
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Retracted: Multimedia Motion of Picking Robot Based on Cooperative Relationship of Matching Gradient Algorithm by Advances in Multimedia

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Enhancing network lifetime in WSNs through coot algorithm-based energy management model by Namita Shinde, Dr. Vinod H․ Patil

Subjects: “…Enhancing Network Lifetime in WSNs through Coot Algorithm-Based Energy Management Model…”
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Hybrid Wind Speed Forecasting Model Study Based on SSA and Intelligent Optimized Algorithm by Wenyu Zhang, Zhongyue Su, Hongli Zhang, Yanru Zhao, Zhiyuan Zhao

“…The present study investigated singular spectrum analysis (SSA) with a reduced parameter algorithm in three time series models, the autoregressive integrated moving average (ARIMA) model, the support vector machine (SVM) model, and the artificial neural network (ANN) model, to forecast the wind speed in Shandong province, China. …”
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Error Estimates from Noise Samples for Iterative Algorithm in Shift-Invariant Signal Spaces by Jun Xian

“…We consider error estimates of iterative algorithm in shift-invariant signal spaces. For the classical sampling and reconstruction algorithm, error estimate from its samples corrupted by white noises are widely studied, but the error analysis of noise with time jitter and iterative noise has not been given as much attention. …”
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Statistical covariance blind detection algorithm based on cholesky factorization in cognitive radio network by Ying-xue LI, Shu-qun SHEN, Lang-tao HU, Qiu-cai WANG

“…As the blind covariance detection algorithm has the shortcoming that the performance parameters are obtained using non-asymptotic method,a new blind detection algorithm was presented using cholesky factorization.Utilizing random matrix theory,the performance parameters was derived using non-asymptotic method.The proposed method overcomes the noise uncertainty problem and performs well without information about the channel,primary user and noise.Numerical simulation results demonstrate that the performance parameters expressions are correct and the new detector outperforms the other blind covariance detectors.…”
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An algorithm for a multicriteria optimization problem and its application to a facility location problem by Nemat Ghafari, M.A. Yaghoobi

“…In this paper, a new algorithm is proposed for solving a multicriteria optimization problem where the feasible set is an $m-$dimensional cube. …”
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