Abstract
The efficient implementation of connected filters is an important issue in signal processing. A typical example is the cascade of two filters, e.g., an adaptive filter with a time-in-variant prefilter. The filtering and adaptation is carried out very efficiently in the frequency domain whenever filters with many coefficients are required. This is implemented as a block algorithm by using overlap-save or overlap-add techniques. However, in many real-time applications also, a short latency time through the system is required, which leads to a degradation of the computational efficiency. Partitioned frequency-domain adaptive filters, also known as multidelay adaptive filters, provide an efficient way for the filtering and adaptation with long filters maintaining short processing delays. This paper shows a computationally efficient way of implementing two or more partitioned frequency-domain filters in cascade or in parallel when their filter lengths are large. The methods presented require only one fast Fourier transform (FFT) and one inverse fast Fourier transform per input and output port, respectively. The FFT size can be even smaller than the length of the filters. The filters can be either time invariant or adaptive.
| Original language | English |
|---|---|
| Pages (from-to) | 685-698 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing |
| Volume | 47 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 2000 |
| Externally published | Yes |
Bibliographical note
Funding Information:Manuscript received July 1999; revised March 2000. This work was supported in part by the Swiss Federal Institute of Technology, ETH Zurich, Switzerland. This paper was recommended by Associate Editor M. Ismail. The authors are with the Signal and Information Processing Laboratory, Swiss Federal Institute of Technology, ETH Zurich, Switzerland. Publisher Item Identifier S 1057-7130(00)06580-0.
Funding
Manuscript received July 1999; revised March 2000. This work was supported in part by the Swiss Federal Institute of Technology, ETH Zurich, Switzerland. This paper was recommended by Associate Editor M. Ismail. The authors are with the Signal and Information Processing Laboratory, Swiss Federal Institute of Technology, ETH Zurich, Switzerland. Publisher Item Identifier S 1057-7130(00)06580-0.
| Funders |
|---|
| Swiss Federal Institute of Technology |
| Eidgenössische Technische Hochschule Zürich |