A Variable Regularization Matrix for the Improved Multiband-Structured Subband Adaptive Filter

作者：Yan Zhen-Hai; Yang Fei-Ran; Yang Jun^*

来源：Acta Electronica Sinica, 2017, 45(8): 2019-2025.

DOI：10.3969/j.issn.0372-2112.2017.08.030

• Convergence rates
• Fast convergence rate
• Misadjustment
• Posteriori error
• Sub-band adaptive filters
• Subband noise
• Tracking capability
• Variable regularization matrix

The conflict between fast convergence rate and small steady-state misadjustment is a problem of the improved multiband-structured subband adaptive filter (IMSAF) algorithm with a fixed regularization factor. Based on the principle of minimizing the system noise, the power of the subband posteriori error is assumed to equal the power of the subband noise. Under this assumption a variable regularization matrix for the IMSAF algorithm is proposed to solve this problem. Simulation results show that the proposed method is superior to the IMSAF algorithm in terms of convergence rate, steady-state misadjustment and tracking capability.

• 出版日期2017