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Estimation of Navigation Mark Floating Based on Fractional-Order Gradient Descent with Momentum for RBF Neural Network

Qionglin Fang, Juan C. Jauregui-Correa
2021 Mathematical Problems in Engineering  
The difference between the later position and the estimated position obtained from the neural network is the error function of the neural network.  ...  The navigation mark's position is taken at a later time as the output of the neural network.  ...  Zouari presented a neural network-based adaptive backstepping dynamic surface control of drug dosage regimens in cancer treatment [21] . e training of neural networks has met some challenges, such as  ... 
doi:10.1155/2021/6681651 fatcat:zfdi5lebtzbctpzmycqqfysjxi

Table of contents

2009 2009 17th Mediterranean Conference on Control and Automation  
The identification method is based on recurrent neural network nonlinear AutoRegressive with eXternal input (NNARX) model derived from dynamic feedforward neural network by adding feedback connection between  ...  The second is the reduction of computational complexity when the number of IF-THEN rules r is control direction. The proposed adaptive neural network control is free of control singularity problem.  ...  The adaptive neural network control laws are developed using state scaling and backstepping without a prior knowledge of the signs of the unknown virtual control coefficients.  ... 
doi:10.1109/med.2009.5164498 fatcat:bi37lbkbhfaihj7lbc64vvplo4