The Experts below are selected from a list of 93 Experts worldwide ranked by ideXlab platform
Changshui Zhang - One of the best experts on this subject based on the ideXlab platform.
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blind source extraction using generalized autocorrelations
IEEE Transactions on Neural Networks, 2007Co-Authors: Zhenwei Shi, Changshui ZhangAbstract:This letter addresses blind (semiblind) source extraction (BSE) problem when a desired source signal has temporal structures, such as linear or nonlinear autocorrelations. Using the temporal characteristics of sources, we develop objective functions based on the generalized autocorrelations of primary sources. Maximizing the objective functions, we propose simple fixed-point source extraction algorithms. We give the stability analysis and prove Convergence properties of the algorithms as the generalized autocorrelation function is linear or nonlinear. Especially, as the generalized autocorrelation function is linear, the algorithm has interesting character of "one-Iteration" Convergence under some conditions. Computer simulations and real-data application experiments show that the algorithms are appealing BSE methods for temporal signals of interest by capturing the linear or nonlinear autocorrelations of the desired sources.
Zhenwei Shi - One of the best experts on this subject based on the ideXlab platform.
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blind source extraction using generalized autocorrelations
IEEE Transactions on Neural Networks, 2007Co-Authors: Zhenwei Shi, Changshui ZhangAbstract:This letter addresses blind (semiblind) source extraction (BSE) problem when a desired source signal has temporal structures, such as linear or nonlinear autocorrelations. Using the temporal characteristics of sources, we develop objective functions based on the generalized autocorrelations of primary sources. Maximizing the objective functions, we propose simple fixed-point source extraction algorithms. We give the stability analysis and prove Convergence properties of the algorithms as the generalized autocorrelation function is linear or nonlinear. Especially, as the generalized autocorrelation function is linear, the algorithm has interesting character of "one-Iteration" Convergence under some conditions. Computer simulations and real-data application experiments show that the algorithms are appealing BSE methods for temporal signals of interest by capturing the linear or nonlinear autocorrelations of the desired sources.
R B Randall - One of the best experts on this subject based on the ideXlab platform.
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very fast blind source separation by signal to noise ratio based stopping threshold for the shibbs sjad algorithm
Mechanical Systems and Signal Processing, 2010Co-Authors: Xianhua Liu, J F Cardoso, R B RandallAbstract:This paper works on joint approximate diagonalization of simplified fourth order cumulant matrices for very fast and large scale blind separation of instantaneous mixing model sources. The JADE algorithm is widely accepted but only limited to small scale separation tasks. The SHIBBS algorithm calculates a fraction of the fourth order cumulant set and avoids eigenmatrix decomposition to reduce calculation cost. However, it was seen to be slower than JADE at the time of its first publication and is hence less known. On the other hand, the SJAD algorithm using the same approach is shown to be very fast. This paper studies the Iteration Convergence criterion and proposes to use a signal to noise ratio based Iteration stopping threshold approach. The improved SHIBBS/SJAD algorithm is very fast, and capable of large scale separation. Experimental separation comparisons between the SHIBBS/SJAD and FastICA are presented.
Weifeng Huang - One of the best experts on this subject based on the ideXlab platform.
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multiple traces surface integral equations for electromagnetic scattering from complex microstrip structures
IEEE Transactions on Antennas and Propagation, 2018Co-Authors: Ran Zhao, Zhixiang Huang, Weifeng HuangAbstract:In this communication, a new multiple-traces Poggio–Miller–Chang–Harrington–Wu–Tsai (MT-PMCHWT) equation is proposed to simulate the electromagnetic scattering from microstrip structures. Based on the surface equivalent principle, the original object can be decomposed into two independent domains, i.e., the exterior region (free space) and interior region (microstrip). Different from the traditional EFIE-PMCHWT method, in this new multiple-traces method, dielectric surface is discretized with two pairs of meshes, and Robin transmission conditions (TCs) are enforced on the interface between the exterior and interior regions to ensure the continuity of fields. In comparison with the traditional EFIE-PMCHWT, this new MT-PMCHWT has a better Iteration Convergence property. Additionally, a new multiple-traces electric field/combined field integral equation with better Iteration Convergence is also proposed. Because the continuity of fields is ensured by TCs, the exterior and interior regions can be discretized with nonconformal meshes, which improves the flexibility and efficiency of the proposed methods substantially.
Dai Ying - One of the best experts on this subject based on the ideXlab platform.
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Iteration Convergence of task load in collaborative product design
Computer Integrated Manufacturing Systems, 2008Co-Authors: Dai YingAbstract:To help designers to plan and adjust design tasks,based on real-time communications among coupled tasks,completion proportion parameter of task load was introduced to represent the collaborative features in product design.Association and function strength of coupled tasks were measured by task adjustment amount in Iteration process.Design structure matrix was transformed to task shift matrix.The overall task load model was constructed.Rules for design process repetition caused by coupling and Iteration Convergence of task load were revealed.According to eigenvector matrix,main influencing factors for Iteration Convergence of task load were defined.By example,the proposed overall task load model and Iteration Convergence rules were verified to be rational and feasible.
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feature of Iteration Convergence in concurrent design
Journal of Chongqing University, 2007Co-Authors: Dai YingAbstract:A parameter,proportion of all work on every task in each stage,is introduced to build a new WTM.Based on this new WTM,this paper deeply analyzes the relationships between the eigenvalue and the Convergence rate of the total work,and the relationships between the eigenvector and the total work.By comparative analysis between the existing WTM and new WTM,it is investigated that this parameter causes the increasing total work and decreasing Convergence rate,and the existing WTM is just a speciality when this parameter becomes the maximum.Finally,the generality of the new WTM is tested by the design process of the camera.
