论文|Yin K L, Pu Y F, Lu L. Hermite Functional Link Artificial Neural Network Assisted Adaptive Algorithms for IoV Nonlinear Active Noise Control

本文原载 IEEE Internet of Things Journal，由四川大学计算机学院蒲亦非教授等科研人员创作，系四川大学“智慧法治”超前部署学科系列学术成果。后续会持续分享四川大学“智慧法治”超前部署学科系列学术成果，欢迎大家阅读。

Abstract: The Internet of Vehicles (IoV) plays a central role in intelligent transportation systems. Components such as motor and transmission in the vehicle may produce noise, which seriously affects comfort. Therefore, vehicle manufacturers attach great importance to active noise control (ANC) technology. However, such ANC system may have some nonlinear distortions in practical, thereby the nonlinear ANC (NANC) system is warranted. Moreover, we consider using IoV for rational resource allocation and record historical data for fault diagnosis, early warning, etc. So far, no work on NANC in the IoV environment is reported. In this paper, based on the Hermite polynomial, a class of functional link artificial neural network (FLANN) algorithms is developed for NANC. The first proposed algorithm, called filtered-h least mean Lp-norm (FhLMP), incorporates the Lp-norm to obtain reliable performance. To further enhance the performance, the recursive FhLMP (RFhLMP) and hyperbolic recursive FhLMP (HRFhLMP) algorithms are designed by formulating two recursive structures. The proposed RFhLMP algorithm takes the filter output as part of the input and is expanded by Hermite FLANN. The HRFhLMP algorithm activates the output by a hyperbolic tangent function and then recursively returns the activated output to the filter input. Simulations verify the improvement of the proposed algorithms for the NANC system.

Keywords: Hermite polynomial,functional link artificial neural network (FLANN),least mean Lp-norm,recursive algorithm,active noise control.

Yin K L, Pu Y F, Lu L. Hermite Functional Link Artificial Neural Network Assisted Adaptive Algorithms for IoV Nonlinear Active Noise Control [J]. IEEE Internet of Things Journal, 2020.（论文下载）