A low computational complexity normalized subband adaptive filter algorithm employing signed regressor of input signal
نویسندگان
چکیده
In this paper, the signed regressor normalized subband adaptive filter (SR-NSAF) algorithm is proposed. This algorithm is optimized by L1-norm minimization criteria. The SR-NSAF has a fast convergence speed and a low steady-state error similar to the conventional NSAF. In addition, the proposed algorithm has lower computational complexity than NSAF due to the signed regressor of the input signal at each subband. The theoretical mean-square performance analysis of the proposed algorithm in the stationary and nonstationary environments is studied based on the energy conservation relation and the steady-state, the transient, and the stability bounds of the SR-NSAF are predicated by the closed form expressions. The good performance of SR-NSAF is demonstrated through several simulation results in system identification, acoustic echo cancelation (AEC) and line EC (LEC) applications. The theoretical relations are also verified by presenting various experimental results.
منابع مشابه
A Family of Variable Step-Size Normalized Subband Adaptive Filter Algorithms Using Statistics of System Impulse Response
This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse response statistics and the optimal step-size vector is obtained by minimizing the mean-square deviation(MSD). In comparison with NSAF, the VSS-NSAF algorithm has faster convergence speed and lower MSD. To reduce the computa...
متن کاملSubband Affine Projection Algorithm for Acoustic Echo Cancellation System
We present a new subband affine projection (SAP) algorithm for the adaptive acoustic echo cancellation with long echo path delay. Generally, the acoustic echo canceller suffers from the long echo path and large computational complexity. To solve this problem, the proposed algorithm combines merits of the affine projection (AP) algorithm and the subband filtering. Convergence speed of the propos...
متن کاملArchitectural Synthesis of Computational Engines for Subband Adaptive Filtering
Architectural synthesis of low-power computational engines (hardware accelerators) for a subband-based adaptive ltering algorithm is presented. The full-band least mean square (LMS) adaptive ltering algorithm, widely used in various applications, is confronted by two problems, viz., slow convergence when the input correlation matrix is ill-conditioned, and increased computational complexity for...
متن کاملAffine projection algorithm for oversampled subband adaptive filters
The performance of the Normalized Least Mean Square (NLMS) algorithm for adaptive filtering is dependent on the spectral flatness of the reference input. Thus, the standard NLMS algorithm does not perform well in Over-Sampled Subband Adaptive Filters (OS-SAFs) because colored subband signals are generated even for white input signals. Thus we propose the use of the Affine Projection Algorithm (...
متن کاملThe New Normalized Subband Adaptive Filter Algorithms with Variable Step - Size Mohammad Shams
This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. In the proposed VSS-NSAF, the step-size changes in order to have largest decrease in the mean square deviation (MSD) for sequential iterations. To reduce the computational complexity of VSS-NSAF, the variable step-size selective partial update normalized subband adaptive filter (VSS-SPU-NSAF) i...
متن کامل