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1. Application of Improved BP Neural Network in Information Fusion Kalman Filter.

Author

Yang, Yu-Hang and Shi, Ying

Subjects
*KALMAN filtering, *PARTICLE swarm optimization, *INFORMATION networks, *WEIGHT training, *ALGORITHMS, *BACK propagation
Abstract

Based on improved back propagation (BP) neural network, information fusion state estimation problem for multi-sensor system is considered. Firstly, particle swarm optimization, search dynamic learning rate and additional momentum method are introduced to train the initial weights and thresholds of BP neural network. Then, the improved neural network is used to optimize the estimated value of Kalman filter. Finally, the sate estimators are fused by weighting matrices. A simulation example verifies the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Published
2020
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