Moritz Harteneck

Design of near perfect reconstruction oversampled filter banks for subband adaptive filters

In this brief, a design algorithm for real-valued and complex-valued oversampled filter banks which yield a low level of inband alias and enable simple subband adaptive structures is presented. The filter banks are either based on complex modulation of a real-valued low-pass prototype or on the direct or modulated setups of real-valued filter banks. If real-valued filter banks are required, then the different channels will have different subsampling ratios so that the bandpass sampling theorem is not violated. This brief also presents design examples of real-valued and complex-valued filter banks.

An oversampled filter bank with different analysis and synthesis filters for the use with adaptive filters

In this paper we propose a real-valued oversampled filter bank where the in-band aliasing is significantly reduced. The connection between the filter bank and the theory of frames is also shown and design algorithms for filter banks implementing general frames and tight frames are presented and design examples are given.

An effective approach to adaptive IIR filtering

An approach to adaptive IIR filtering based on a pseudo-linear regression and a QR matrix decomposition is developed. The algorithm has proved to be stable and has good convergence properties if the unknown system satisfies the strictly positive real condition. The derivation of the algorithm is straightforward and the computational complexity is less than the computational complexity of the IIR-RPE algorithm. Simulation results of system identification with synthetic and real world data are shown comparing the algorithm with the IIR-RPE and the IIR-LMS algorithm.

Adaptive IIR filtering using QR matrix decomposition

In this correspondence, an approach to adaptive IIR filtering based on a pseudo-linear regression and applying an iterative QR matrix decomposition is developed. In simulations, the algorithm has shown a high stability and excellent convergence properties. The derivation of the IIR-QR adaptive filter is straightforward, and the computational complexity of the algorithm is comparable with the FIR-QR adaptive algorithm of the same order and less than gradient-based adaptive IIR filters such as the simplified-gradient recursive prediction error (RPE) algorithm. Fast versions of O(N) computational complexity are readily available.

Rapid prototyping library for adaptive signal processing applications

In this paper we present a library for the rapid prototyping of adaptive signal processing algorithms, architectures and applications. The library is hosted by the DSP simulation software SystemView and covers virtually the complete spectrum of linear, and non-linear adaptive algorithms currently in use in contemporary DSP and communications applications. The library can be easily used with real signals, with variable system wordlengths, sampling frequencies and so on. Therefore in this paper we discuss the design philosophy behind the library and overview the various algorithms and applications that are implemented. The paper shows an implementation of an adaptive multiuser CDMA receiver/decision feedback equaliser (DFE) as an example of the relevance and rapid development that is possible. Copies of the library and example files can be downloaded from the Web following the instructions in the paper.

A teaching and evaluation tool for adaptive signal processing using Java

A teaching and evaluation tool for adaptive algorithms using the Java platform is presented. The tool has been developed for use in teaching adaptive signal processing and gives the students the facility to observe a comprehensive set of algorithms executing in the time, frequency and z-domain, vary any parameter and thereby augment the traditional learning process. Another key aim in the development was to provide a simple tool so that the feasibility of adaptive algorithms for a particular problem can be evaluated quickly. The Java platform has been chosen for this task since it is possible to run the tool on any computer system (e.g. Unix, Windows, Linux) using a Java virtual machine via the World Wide Web.

Polyphase analysis of subband adaptive filters

Based on a polyphase analysis of a subband adaptive filter (SAF) system, it is possible to calculate the optimum subband impulse responses to which the SAF system will converge. We give some insight into how these optimum impulse responses are calculated, and discuss two applications of our technique. Firstly, the performance limitations of an SAF system can be explored with respect to the minimum mean square error performance. Secondly, fullband impulse responses can be correctly projected into the subband domain, which is required for example for translating constraints for subband adaptive beamforming. Examples for both applications are presented.

An estimation algorithm for AR models with closely located lightly damped low frequency poles

We present a pole estimation algorithm which is based on an overdetermined adaptive IIR filter with an additional postprocessing stage to extract the pole locations from the adaptive weights. The adaptive filtering algorithm used, is a pseudo-linear regression algorithm which is solved by a time-recursive QR decomposition. Two pole classification schemes are presented to separate the true poles and the superfluous poles. The classification schemes are based on the occurrence of pole-zero cancelation and on the pole movement in the z-plane. Floating point simulations are presented to demonstrate the performance of the proposed algorithm.