Adaptive Filters Revisited - RFI Mitigation in pulsar observations

Pulsar detection and timing experiments are applications where adaptive filters seem eminently suitable tools for radio-frequency-interference (RFI) mitigation. We describe a novel variant which works well in field trials of pulsar observations centred on an observing frequency of 675 MHz, a bandwidth of 64 MHz and with 2-bit sampling. Adaptive filters have generally received bad press for RFI mitigation in radio astronomical observations with their most serious drawback being a spectral echo of the RFI embedded in the filtered signals. Pulsar observations are intrinsically less sensitive to this as they operate in the (pulsar period) time domain. The field trials have allowed us to identify those issues which limit the effectiveness of the adaptive filter. We conclude that adaptive filters can significantly improve pulsar observations in the presence of RFI.Comment: Accepted for publication in Radio Scienc

Performance limitations of subband adaptive filters

In this paper, we evaluate the performance limitations of subband adaptive filters in terms of achievable final error terms. The limiting factors are the aliasing level in the subbands, which poses a distortion and thus presents a lower bound for the minimum mean squared error in each subband, and the distortion function of the overall filter bank, which in a system identification setup restricts the accuracy of the equivalent fullband model. Using a generalized DFT modulated filter bank for the subband decomposition, both errors can be stated in terms of the underlying prototype filter. If a source model for coloured input signals is available, it is also possible to calculate the power spectral densities in both subbands and reconstructed fullband. The predicted limits of error quantities compare favourably with simulations presented

On the optimality of subband adaptive filters

In this paper, we derive a polyphase analysis to determine the optimum filters in a subband adaptive filter (SAF) system. The structure of this optimum solution deviates from the standard SAF approach and presents its best possible solution only as an approximation. Besides this new insight into SAF error sources, the discussed analysis allows to calculate the optimum subband responses and the standard SAF approximation. Examples demonstrating the validity of our analysis and its use for determining SAF errors are presented

Memristive Adaptive Filters

Using the memristive properties of vanadium dioxide, we experimentally demonstrate an adaptive filter by placing a memristor into an LC contour. This circuit reacts to the application of select frequency signals by sharpening the quality factor of its resonant response, and thus “learns” according to the input waveform. The proposed circuit employs only analog passive elements, and may find applications in biologically inspired processing and information storage. We also extend the learning-circuit framework mathematically to include memory-reactive elements, such as memcapacitors and meminductors, and show how this expands the functionality of adaptive memory filters