Optimal Detection of Sparse Signal Segments

In many applications involving high dimensional data, we are interested in identifying sparse segments of signal in a noisy background. The signals can be copy number variation, or objects in video surveillance among others. We study the relationship between the detectability of a signal, and its shape as well as duration; and the implications of such a relationship on detection strategies.