An efficient, approximate path-following algorithm for elastic net based nonlinear spike enhancement

Max A. Little*

*Corresponding author for this work

    Research output: Chapter in Book/Published conference outputConference publication


    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.

    Original languageEnglish
    Title of host publication2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO)
    Number of pages5
    ISBN (Print)978-0-9928626-1-9
    Publication statusPublished - 2014
    Event22nd European Signal Processing Conference - Lisbon, Portugal
    Duration: 1 Sept 20145 Sept 2014


    Conference22nd European Signal Processing Conference
    Abbreviated titleEUSIPCO 2014

    Bibliographical note

    © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    Funding: Wellcome Trust (Grant WT090651MF)


    • filter
    • noise
    • nonlinear
    • regularization
    • spike


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