Acoustic coupling in communication devices poses a substantial threat to voice communication fidelity primarily due to the emergence of echo problems. Conventional adaptive filtering algorithms based on mean square error (MSE) exhibit critical stability limitations under non-Gaussian interference conditions, particularly when confronted with concurrency of impulsive noise disturbances and time-varying double-talk scenarios. To address this problem, this paper proposes a non-canonical finite impulse response (NCFIR) structure based on the maximum versoria criterion (MVC), termed NCMVC. The NCMVC enhances robustness and reduces system latency by strategically reconstructing critical signal processing paths. Distinct from conventional FIR filters, the proposed NCFIR architecture optimizes delay paths, enabling high-frequency real-time processing. Additionally, the MVC-based adaptation ensures robust convergence even in impulsive noise scenarios. Simulation results demonstrate the superior performance of the NCMVC algorithm compared to existing approaches.

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Non-canonical Adaptive Filters Driven by Maximum Versoria Criterion

  • Yifei Wang,
  • Kaili Yin,
  • Shaoyuan Li,
  • Wentao Liu

摘要

Acoustic coupling in communication devices poses a substantial threat to voice communication fidelity primarily due to the emergence of echo problems. Conventional adaptive filtering algorithms based on mean square error (MSE) exhibit critical stability limitations under non-Gaussian interference conditions, particularly when confronted with concurrency of impulsive noise disturbances and time-varying double-talk scenarios. To address this problem, this paper proposes a non-canonical finite impulse response (NCFIR) structure based on the maximum versoria criterion (MVC), termed NCMVC. The NCMVC enhances robustness and reduces system latency by strategically reconstructing critical signal processing paths. Distinct from conventional FIR filters, the proposed NCFIR architecture optimizes delay paths, enabling high-frequency real-time processing. Additionally, the MVC-based adaptation ensures robust convergence even in impulsive noise scenarios. Simulation results demonstrate the superior performance of the NCMVC algorithm compared to existing approaches.