Recently a new real-valued oversampled filter bank has been proposed which reduces the “inband” alias. The filter bank consists of at least three channels which are subsampled by different subsampling ratios. In this paper we investigate into the applicability of this filter bank for adaptive subband filtering and compare the setup with existing subband and fullband techniques.

In this paper, we present a new image denoising method based on adaptive subband decomposition (or adaptive wavelet transform) in which the filter coefficients are updated according to an Least Mean Square (LMS) type algorithm. Adaptive subband decomposition filter banks have the perfect reconstruction property. Since the adaptive filterbank adjusts itself to the changing input environments den...

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...

In this paper, we propose subband adaptive array processing for mitigation of both intersymbol interference (ISI) and cochannel interference (CCI) in digital mobile communications. Subband adaptive array processing employs filter banks in a front end to an adaptive array receiver. By decomposing the signals into a set of subband signals, the analysis filters enhance the correlation of multipath...

The subband adaptive filter system has been applied to the acoustic echo cancellation problem in order to overcome the problems of slow convergence due to spectrally dynamic input and high computational costs associated with a single, long adaptive filter. Research into the convergence characteristics of subband acoustic echo cancelers (AECs) have either used Gaussian white noise, USASI noise (...

Subband adaptive filters have been proposed to avoid the drawbacks of slow convergence and high computational complexity associated with time domain adaptive filters. Subband processing introduces transmission delays caused by the filter bank and signal degradations due to aliasing effects. One efficient way to reduce the aliasing effects is to allow a higher sample rate than critically needed ...

In hands-free telephone systems, the received speech signal is fed back to the microphone and constitutes the so-called echo. To cancel the effect of this time-varying echo path, it is necessary to device an adaptive filter between the receiving and the transmitting ends. For a typical FIR realization, the length of the fullband adaptive filter results in high computational complexity and low c...

Subband adaptive filters have been proposed to avoid the drawbacks of slow convergence and high computational complexity associated with time domain adaptive filters. Subband processing introduces transmission delays caused by the filter bank and signal degradations due to aliasing effects. One efficient way to reduce the aliasing effects is to allow a higher sample rate than critically needed ...

Subband adaptive filtering (SAF) generally employs multirate filter banks for signal decomposition and reconstruction. This technique allows for fast convergence and reduced computational complexity through use of the robust least mean squares (LMS) algorithm in acoustic environments. However, the performance of subband adaptive schemes is often degraded by artifacts introduced by the insertion...

Some convergence properties of an adaptive filter structure which employs an analysis filter bank and sparse adaptive subfilters are investigated in this paper. By properly choosing the filter bank and the number of adaptive coefficients, such a structure is capable of modeling any linear system with finite impulse response (FIR). Using the analysis results derived in this paper, an optimizatio...