Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Adaptive feedback cancellation in hearing aids with linear prediction of the desired signal
IEEE Transactions on Signal Processing - Part I
The behavior of LMS and NLMS algorithms in the presence ofspherically invariant processes
IEEE Transactions on Signal Processing
Convergence behavior of affine projection algorithms
IEEE Transactions on Signal Processing
An efficient robust adaptive filtering algorithm based on parallelsubgradient projection techniques
IEEE Transactions on Signal Processing
Adaptive Parallel Quadratic-Metric Projection Algorithms
IEEE Transactions on Audio, Speech, and Language Processing
Convex set theoretic image recovery by extrapolated iterations of parallel subgradient projections
IEEE Transactions on Image Processing
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Acoustic feedback is an important factor that degrades the overall performance of hearing aids, and acoustic feedback cancellation has always been the research focus in the field of signal processing in hearing aids. The newly suggested adaptive projection subgradient method (APSM) for adaptive signal processing solves the problem of difficulty in finding the exact projection operator in the realization of affine projection by taking the subgradient projection hyperplane as the searching region for relaxed projection. This work applies APSM in the acoustic feedback cancellation system of hearing aids for the first time, and proposes a weighted adaptive projection subgradient method (WAPSM), which takes into consideration the exponential decay weight factor to incorporate the prior information of estimation system. The new method is compared with the traditional NLMS algorithm and APSM algorithm in simulation experiments. Incorporating the prior information of estimation system by setting the proper weighting matrix, WAPSM achieved notable improvements on the speed, stability and accuracy of the misalignment convergence. Numerical experiments demonstrate that the proposed algorithm is more robust for low SNR and real speech segment input than the traditional algorithms.