title: Deconvolution of pulse trains with the L0 penalty.
abstract: The output of many instruments can be modeled as a convolution of an impulse response and a series of sharp spikes. Deconvolution considers the inverse problem: estimate the input spike train from an observed (noisy) output signal. We approach this task as a linear inverse problem, solved using penalized regression. We propose the use of an L(0) penalty and compare it with the more common L(2) and L(1) penalties. In all cases a simple and iterative weighted regression procedure can be used. The model is extended with a smooth component to handle drifting baselines. Application to three different data sets shows excellent results.
authors.affiliation: Department of Bioinformatics, Erasmus Medical Center, Rotterdam, The Netherlands. j.derooi@erasmusmc.nl
authors.forename: Johan
authors.initials: J
authors.lastname: de Rooi
authors.forename: Paul
authors.initials: P
authors.lastname: Eilers
mesh_terms: D002849:Chromatography, Gas / Q000379:methods*; D006801:Humans; D007986:Luteinizing Hormone / Q000097:blood*; D015233:Models, Statistical; D012044:Regression Analysis; D017422:Sequence Analysis, DNA / Q000379:methods*
chemical_list: D007986:Luteinizing Hormone