Nonlinear system identification using IIR Spline Adaptive Filters

2015 ◽  
Vol 108 ◽  
pp. 30-35 ◽  
Author(s):  
Michele Scarpiniti ◽  
Danilo Comminiello ◽  
Raffaele Parisi ◽  
Aurelio Uncini
2021 ◽  
Author(s):  
Qianqian Liu ◽  
Yigang He

Abstract This paper primarily proposes a family of quaternion Volterra filters based on the feedforward pipelined structure (QPSOVAFs) for nonlinear quaternion system identification to reduce the computational complexity. Then, the strictly nonlinear QPSOVAF (SNL-QPSOVAF), semi-widely nonlinear QPSOVAF(SWNL-QPSOVAF), and widely nonlinear QPSOVAF (WNL-QPSOVAF), are proposed. This architecture consists of several quaternion-valued second-order Volterra (SOV) modules. The structure's nonlinear subsection executes a nonlinear mapping from the input space to an intermediate space using the feedforward SOV; the linear combiner subsection performs a linear mapping from the intermediate space to the output space. Moreover, the theoretical analysis expresses the effectiveness of the proposed QPSOVAFs in a specific condition. Finally, simulation results further prove that the proposed QPSOVAFs have good performance in identifying the quaternion-valued nonlinear system.


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