A Proportionate Maximum Total Complex Correntropy Algorithm for Sparse Systems
While the practical application of adaptive filters has indeed garnered substantial attention, two pressing issues persist that have a profound impact on their performance—system sparsity and the presence of contaminated Gaussian impulsive noise. In this research paper, we propose a novel approach t...
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| Veröffentlicht in: | Circuits, systems, and signal processing systems, and signal processing, 2024-10, Vol.43 (10), p.6415-6436 |
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| container_title | Circuits, systems, and signal processing |
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| creator | Huang, Sifan Liu, Junzhu Qian, Guobing Wang, Xin |
| description | While the practical application of adaptive filters has indeed garnered substantial attention, two pressing issues persist that have a profound impact on their performance—system sparsity and the presence of contaminated Gaussian impulsive noise. In this research paper, we propose a novel approach to tackle both of these issues simultaneously by introducing the concept of a proportionate matrix. Specifically, we present a proportionate maximum total complex correntropy algorithm based on the errors-in-variables model. The paper presents a theoretical analysis of the steady-state weight error power under the influence of impulsive noise. Furthermore, it discusses the performance comparison in system identification and highlights the robustness of the proposed algorithm. To validate its effectiveness, a simulation involving stereophonic acoustic echo cancellation is conducted, and the results confirm the clear advantages of the proposed Proportionate Maximum Total Complex Correntropy algorithm. |
| doi_str_mv | 10.1007/s00034-024-02752-9 |
| format | Article |
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| subjects | Acoustics Adaptive algorithms Adaptive filters Adaptive systems Algorithms Circuits and Systems Complex variables Electrical Engineering Electronics and Microelectronics Engineering Error analysis Instrumentation Signal processing Signal,Image and Speech Processing Simulation Sparsity Steady state models System identification Variables |
| title | A Proportionate Maximum Total Complex Correntropy Algorithm for Sparse Systems |
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