Unwanted spike noise in a digital signal is a common problem in digital filtering. However, sometimes the spikes are wanted and other, superimposed, signals are unwanted, and linear, time invariant (LTI) filtering is ineffective because the spikes are wideband - overlapping with independent noise in the frequency domain. So, no LTI filter can separate them, necessitating nonlinear filtering. However, there are applications in which the noise includes drift or smooth signals for which LTI filters are ideal. We describe a nonlinear filter formulated as the solution to an elastic net regularization problem, which attenuates band-limited signals and independent noise, while enhancing superimposed spikes. Making use of known analytic solutions a novel, approximate path-following algorithm is given that provides a good, filtered output with reduced computational effort by comparison to standard convex optimization methods. Accurate performance is shown on real, noisy electrophysiological recordings of neural spikes.
|Title of host publication||2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO)|
|Number of pages||5|
|Publication status||Published - 2014|
|Event||22nd European Signal Processing Conference - Lisbon, Portugal|
Duration: 1 Sep 2014 → 5 Sep 2014
|Conference||22nd European Signal Processing Conference|
|Abbreviated title||EUSIPCO 2014|
|Period||1/09/14 → 5/09/14|
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Funding: Wellcome Trust (Grant WT090651MF)