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Development of Hartley domain filtered-s LMS algorithm for active noise control system

机译:用于主动噪声控制系统的Hartley Domain过滤器LMS算法的研制

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Active noise control of the nonlinear noise processes uses nonlinear control structures such as Volterra filter or different kinds of neural networks. Filtered-s LMS (FSLMS) algorithm is a recently proposed algorithm, which uses functional link artificial neural network as its control structure. It is seen that filtered-s LMS algorithm outperforms the ANC algorithms like FXLMS and also the Volterra filtered-x LMS (VFXLMS) under higher order nonlinearity case. It is also seen that the nonlinear ANC algorithms like FSLMS or VFXLMS algorithms involves higher computational complexity than the linear ANC algorithm such as FXLMS algorithm. In this paper, Hartley transform is used to implement exactly the same FSLMS algorithm involving lesser number of computations.
机译:非线性噪声过程的主动噪声控制使用非线性控制结构,例如Volterra滤波器或不同种类的神经网络。过滤器LMS(FSLMS)算法是最近提出的算法,其使用功能链路人工神经网络作为其控制结构。可以看出,过滤器的LMS算法优于FXLMS等ANC算法以及在高阶非线性情况下的Volterra Filtered-X LMS(VFXM)。还可以看出,FSLMS或VFXLMS算法等非线性ANC算法涉及比诸如FXLMS算法的线性ANC算法更高的计算复杂度。在本文中,Hartley变换用于实现涉及较少计算数量的相同的FSLMS算法。

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