Abstract
The adaptive algorithms have been widely studied in Gaussian environment. However, the impulsive noise and other non-Gaussian noise may largely deteriorate the performance of algorithm in practical applications. To address this problem, in this paper, we propose two novel adaptive algorithms for system identification problem with mixed noise scenarios. Both proposed algorithms are based on the framework of the affine projection (AP) algorithm. The first proposed algorithm, termed as VS-APMCCA, combines variable step-size (VS) strategy and maximum correntropy criterion (MCC) to obtain improved performance. For further performance improvement, the VC-VS-APMCCA is developed, which is based on the variable center (VC) scheme of MCC. The convergence analysis of the VC-VS-APMCCA is conduced. Finally, simulation results demonstrate the superior performance of the VS-APMCCA and VC-VS-APMCCA.
Highlights
Adaptive filtering technique has been successfully applied in diverse signal processing fields, such as active noise control, system identification, and adaptive echo cancellation [1]–[3]
1) A novel variable step-size (VS)-APMCCA is proposed by using high-order error power criterion (HOEP) and VS scheme, which enables the proposed VS-APMCCA to obtain anti-impulsive ability of maximum correntropy criterion (MCC) algorithm and the fast convergence rate of the APA; 2) A novel variable center (VC)-VS-APMCCA is developed as an added contribution, with an adjustable center position; 3) Convergence behavior of the VC-VS-APMCCA is analyzed; 4) Simulations are performed to demonstrate the effectiveness of the VS-APMCCA and VC-VS-APMCCA
In this paper, we have proposed two novel affine projection (AP) algorithms based on MCC and VC strategy for performance improvement in system identification with mixed noise
Summary
Adaptive filtering technique has been successfully applied in diverse signal processing fields, such as active noise control, system identification, and adaptive echo cancellation [1]–[3]. Several APSA-based algorithms were proposed by using variable step-size (VS) scheme [12]–[14], convex combination strategy [15] and so on. A VC-VS-APMCCA is proposed based on VC scheme to further enhance the identification accuracy of the adaptive algorithm. 1) A novel VS-APMCCA is proposed by using HOEP and VS scheme, which enables the proposed VS-APMCCA to obtain anti-impulsive ability of MCC algorithm and the fast convergence rate of the APA; 2) A novel VC-VS-APMCCA is developed as an added contribution, with an adjustable center position; 3) Convergence behavior of the VC-VS-APMCCA is analyzed; 4) Simulations are performed to demonstrate the effectiveness of the VS-APMCCA and VC-VS-APMCCA. The a priori error e(k) is employed to replace the a posteriori error ep(k) during weight adaptation This approximation is widely applied to the derivation of the APA-based algorithms, and the similar method can be found in [11].
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