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A recurrent neural network for online design of robust optimal filters
journal contribution
posted on 2023-05-16, 16:37 authored by Jiang, D, Wang, JA recurrent neural network is developed for robust optimal filter design. The purpose is to fill the gap between the real-time computation requirement in practice and the computational complexity of the filter design in the case that the statistical properties of noise are unknown. First, an H∞ requirement and an L2 requirement of filter design problem are formulated as a group of linear matrix inequalities. On this basis, an optimization problem is introduced to solve the robust optimal filter design problem. Then, a recurrent neural network is deliberately developed for solving the optimization problem in real time. The effectiveness and efficiency of the recurrent neural network is shown by use of theoretical and simulation results. © 2000 IEEE.
History
Publication title
IEEE Transactions on Circuits and Systems Part 1: Fundamental Theory and ApplicationsVolume
47Issue
6Pagination
921-926ISSN
1057-7122Department/School
School of EngineeringPublisher
Institute of Electrical and Electronics Engineers, IncPlace of publication
United StatesRepository Status
- Restricted