1. Modified Newton Integration Neural Algorithm for Dynamic Complex-Valued Matrix Pseudoinversion Applied to Mobile Object Localization
- Author
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Huan Wang, Yangyang Ning, Shan Liao, Haoen Huang, Long Jin, Dongyang Fu, and Xiuchun Xiao
- Subjects
Artificial neural network ,Computer science ,Iterative method ,020208 electrical & electronic engineering ,02 engineering and technology ,Workspace ,Computer Science Applications ,Matrix (mathematics) ,Control and Systems Engineering ,Robustness (computer science) ,0202 electrical engineering, electronic engineering, information engineering ,Noise (video) ,Electrical and Electronic Engineering ,Algorithm ,Information Systems - Abstract
A dynamic complex-valued matrix pseudoinversion (DCVMP) is encountered in some special environments, where the system parameters contain the dynamic, magnitude, and phase information. Currently, most of the existing models are employed to the DCVMP under a noise-free workspace. However, the noise perturbation is unavoidable in the practical application scenarios. Therefore, the motivation of this article is to design a computational model for the DCVMP with strong robustness and high-precision computing solutions. To this end, a modified Newton integration (MNI) neural algorithm is proposed for the DCVMP with noise-suppressing ability in this article. Besides, the corresponding convergence proofs on the MNI neural algorithm are provided. Furthermore, the numerical simulations and an application to the estimation of mobile object localization, are demonstrated to illustrate the superiority of the MNI neural algorithm.
- Published
- 2021
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