Maximum entropy properties of discrete-time first-order stable spline kernel
2016 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 66, 34-38 p.Article in journal (Refereed) Published
The first order stable spline (SS-1) kernel (also known as the tunedcorrelated kernel) is used extensively in regularized system identification, where the impulse response is modeled as a zero-mean Gaussian process whose covariance function is given by well designed and tuned kernels. In this paper, we discuss the maximum entropy properties of this kernel. In particular, we formulate the exact maximum entropy problem solved by the SS-1 kernel without Gaussian and uniform sampling assumptions. Under general sampling assumption, we also derive the special structure of the SS-1 kernel (e.g. its tridiagonal inverse and factorization have closed form expression), also giving to it a maximum entropy covariance completion interpretation.
Place, publisher, year, edition, pages
2016. Vol. 66, 34-38 p.
System identification;Regularization method;Kernel structure;Maximum entropy
IdentifiersURN: urn:nbn:se:liu:diva-121618DOI: 10.1016/j.automatica.2015.12.009OAI: oai:DiVA.org:liu-121618DiVA: diva2:857316