Nonlinear Adaptive Filter Based on Pipelined Bilinear Function Link Neural Networks Architecture

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.