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Spatial shrinkage via the product independent Gaussian process prior
[article]
2020
arXiv
pre-print
We study the problem of sparse signal detection on a spatial domain. We propose a novel approach to model continuous signals that are sparse and piecewise smooth as product of independent Gaussian processes (PING) with a smooth covariance kernel. The smoothness of the PING process is ensured by the smoothness of the covariance kernels of Gaussian components in the product, and sparsity is controlled by the number of components. The bivariate kurtosis of the PING process shows more components in
arXiv:1805.03240v4
fatcat:747d72vtfnfbpbgdmasd47cyqe