An adaptive microwave photonic angle-of-arrival(AOA) estimation approach based on a convolutional neural network with a bidirectional gated recurrent unit(BiGRU-CNN) is proposed and *** with the previously reported AO...
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An adaptive microwave photonic angle-of-arrival(AOA) estimation approach based on a convolutional neural network with a bidirectional gated recurrent unit(BiGRU-CNN) is proposed and *** with the previously reported AOA estimation methods based on phase-to-power mapping,the proposed method is unnecessary to know the frequency of the signal under test(SUT) in *** envelope voltage correlation matrix is obtained from dual-drive Mach–Zehnder modulator(N-DDMZM,N > 2) optical interferometer arrays first,and then AOA estimations are performed on different frequency signals with the aid of BiGRU-CNN.A three-DDMZM-based experiment is carried out to assess the estimation performance of microwave signals at three different frequencies,and the mean absolute error is only 0.1545°.
A unified a posteriori error analysis has been developed in [18, 21-23] to analyze the finite element error a posteriori under a universal roof. This paper contributes to the finite element meshes with hanging nodes w...
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A unified a posteriori error analysis has been developed in [18, 21-23] to analyze the finite element error a posteriori under a universal roof. This paper contributes to the finite element meshes with hanging nodes which are required for local mesh-refining. The twodimensional 1-irregular triangulations into triangles and parallelograms and their combinations are considered with conforming and nonconforming finite element methods named after or by Courant, Q1, Crouzeix-Raviart, Poisson, Stokes and Navier-Lamé equations Han, Rannacher-Turek, and others for the The paper provides a unified a priori and a posteriori error analysis for triangulations with hanging nodes of degree ≤ 1 which are fundamental for local mesh refinement in self-adaptive finite element discretisations.
For eddy current nondestructive testing (ECNDT). an immune genetic algorithm.(1GA) is presented, which can overcome the disadvantages of genetic algorithm.(GA), such as the possibility of being trapped on locally mini...
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For eddy current nondestructive testing (ECNDT). an immune genetic algorithm.(1GA) is presented, which can overcome the disadvantages of genetic algorithm.(GA), such as the possibility of being trapped on locally minimum value and premature convergence. Moreover, crossover and mutation operators are selected by adaptive algorithm.to overcome prematurity. Compared with GA. the convergence precision and generalization of IGA are improved remarkably.
This paper describes a new, auto-adaptive algorithm.for dead reckoning in DIS. In general dead-reckoning algorithm. use a fixed threshold to control the extrapolation errors. Since a fixed threshold cannot adequately ...
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ISBN:
(纸本)9780769501550
This paper describes a new, auto-adaptive algorithm.for dead reckoning in DIS. In general dead-reckoning algorithm. use a fixed threshold to control the extrapolation errors. Since a fixed threshold cannot adequately handle the dynamic relationships between moving entities, a multi-level threshold scheme is proposed. The definition of threshold levels is based on the concepts of area of interest (AOI) and sensitive region (SR), and the levels of threshold are adaptively adjusted based on the relative distance between entities during the simulation. Various experiments were conducted. The results show that the proposed auto-adaptive dead reckoning algorithm.can achieve considerable reduction in update packets without sacrificing accuracy in extrapolation.
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