Identifying the support of rectangular signals in Gaussian noise

Abstract

We consider the problem of identifying the support of the block signal in a sequence when both the length and the location of the block signal are unknown. The multivariate version of this problem is also considered, in which we try to identify the support of the rectangular signal in a hyper-rectangle. In this article, we greatly generalize the requirement in Jeng, Cai, and Li and in particular, we allow the length of the block signal to grow polynomially with the length of the sequence. A statistical boundary above which the identification is possible is presented and an asymptotically optimal and computationally efficient procedure is proposed under the assumption of Gaussian white noise. The problem of block signal identification is shown to have the same statistical difficulty as the corresponding problem of detection, in the sense that whenever we can detect the signal, we can identify the support of the signal. Some generalizations are also considered here: (1) the case of multiple block signals, (2) the robust identification problem where the noise distribution is unspecified, (3) the block signal identification problem under the exponential family setting.