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Noise-tolerate and adaptive coefficient zeroing neural network for solving dynamic matrix square root

CAAI Transactions on Intelligence Technology 2024年第1期9卷 167-177页

作者： Xiuchun Xiao Chengze Jiang Qixiang Mei Yudong Zhang School of Electronics and Information Engineering Guangdong Ocean UniversityZhanjiangChina School of Cyber Science and Engineering Southeast UniversityNanjingChina School of Computing and Mathematical Sciences University of LeicesterLeicesterUK

The solving of dynamic matrix square root(DMSR)problems is frequently encountered in many scientific and engineering *** the original zeroing neural network is powerful for solving the DMSR,it cannot vanish the influence of the noise perturbations,and its constant-coefficient design scheme cannot accelerate the convergence ***,a noise-tolerate and adaptive coefficient zeroing neural network(NTACZNN)is raised to enhance the robust noise immunity performance and accelerate the conver-gence speed ***,the global convergence and robustness of the pro-posed NTACZNN are theoretically analysed under an ideal environment and noise-perturbed ***,some illustrative simulation examples are designed and performed in order to substantiate the efficacy and advantage of the NTACZNN for the DMSR problem *** with some existing ZNNs,the proposed NTACZNN possesses advanced performance in terms of noise tolerance,solution accuracy,and convergence rate.

关键词： adaptive intelligent systems neural network real-time systems

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Optimal fusion‐based localization method for tracking of smartphone user in tall complex buildings

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1104-1123页

作者： Harun Jamil Do‐Hyeun Kim Department of Electronics Engineering Jeju National UniversityJeju‐SiRepublic of Korea Department of Computer Engineering Jeju National UniversityJeju‐SiRepublic of Korea

In the event of a fire breaking out or in other complicated situations,a mobile computing solution combining the Internet of Things and wearable devices can actually assist tracking solutions for rescuing and evacuating people in multistory ***,it is crucial to increase the positioning technology's *** sequential Monte Carlo(SMC)approach is used in various applications such as target tracking and intelligent surveillance,which rely on smartphone‐based inertial data ***,the SMC method has intrinsic flaws,such as sample impoverishment and particle degeneracy.A novel SMC approach is presented,which is built on the weighted differential evolution(WDE)*** Monte Carlo approaches start with random particle placements and arrives at the desired distribution with a slower variance reduction,like in a high‐dimensional space,such as a multistory *** differential evolution is included before the resampling procedure to guarantee the appropriate variety of the particle set,prevent the usage of an inadequate number of valid samples,and preserve smartphone user position *** values of the smartphone‐based sensors and BLE‐beacons are set as input to the SMC,which aids in fast approximating the posterior distributions,to speed up the particle congregation process in the proposed SMC‐based WDE ***,the robustness and efficacy of the suggested technique more accurately reflect the actual situation of smartphone *** to simulation findings,the suggested approach provides improved location estimation with reduced localization error and quick *** results confirm that the proposed optimal fusion‐based SMC‐WDE scheme performs 9.92%better in terms of MAPE,15.24%for the case of MAE,and 0.031%when evaluating based on the R2 Score.

关键词： 2‐D adaptive intelligent systems adaptive systems artificial immune system artificial intelligence techniques

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