Nonlinear Adaptive Filter Based on Pipelined Bilinear Function Link Neural Networks Architecture
Authors: Dinh Cong Le, Van Minh Le, Thai Son Dang, The Anh Mai, Manh Cuong Nguyen
The International Conference on Intelligent Systems & Networks
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Publishing year: 5/2021
In order to further enhance the computational efficiency and application scope of the bilinear functional links neural networks (BFLNN) filter, a pipelined BFLNN (PBFLNN) filter has been developed in this paper. The idea of the method is to divide the complex BFLNN structure into multiple simple BFLNN modules (with a smaller memory-length) and cascade connection in a pipelined fashion. Thanks to the simultaneous processing and the nested nonlinearity of the modules, the PBFLNN achieves a significant improvement in computation without degrading its performance. The simulation results have demonstrated the effectiveness of the proposed method and the potentials of the PBFLNN filter in many different applications.
