The New Normalized Subband Adaptive Filter Algorithms with Variable Step-Size

Abstract

Original scientific paperThis 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) is proposed. In this algorithm the filter coefficients are partially updated in each subband at every iteration. Simulation results show the good performance of the proposed algorithms in convergence speed and steady-state MSD.

The Variable Step-Size Wavelet Transform-Domain LMS Adaptive Filter Algorithm

“…Also, the theoretical performance analysis is presented in the next section. To do so, the following assumptions are made throughout the paper [8], [20], [21], [22], [23], [24], [25], [26].…”

“…One of the most important strategy in this issue was presented in [16]. This approach was successfully extended to the different adaptive filter algorithms [17], [18], [19], [20].…”

“…In [20], the variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm was introduced. The VSS-NSAF had faster convergence speed than NSAF.…”

“…But, the computational complexity of VSS-NSAF was significantly higher than NSAF. On the other hand, the theoretical performance analysis of VSS-NSAF was not studied in [20]. It means that any theoretical relations were not presented for VSS-NSAF in the stationary and nonstationary environments.…”