Regularized spectrum estimation in spaces induced by stable spline kernels

G. Bottegal, G. Pillonetto

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


We introduce a new kernel-based nonparametric approach to estimate the second-order statistics of scalar and stationary stochastic processes. The correlations functions are assumed to be summable and are modeled as realizations of zero-mean Gaussian processes using the recently introduced Stable Spline kernel. In this way, information on the decay to zero of the functions to reconstruct is included in the estimation process. The overall complexity of the proposed algorithm scales linearly with the number of available samples of the processes. Numerical experiments show that the method compares favorably with respect to classical nonparametric spectral analysis approaches with an oracle-type choice of the parameters.
Original languageEnglish
Title of host publication2012 American Control Conference (ACC), 27-29 June 2012, Montreal, Canada
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)978-1-4577-1096-4
ISBN (Print)978-1-4577-1095-7
Publication statusPublished - 2012
Externally publishedYes
Event2012 American Control Conference, ACC 2012 - Fairmont Queen Elizabeth, Montreal, Canada
Duration: 27 Jun 201229 Jun 2012


Conference2012 American Control Conference, ACC 2012
Abbreviated titleACC 2012
Internet address


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