Phase Transitions with Structured Sparsity

Abstract

In the field of signal processing, phase transition phenomena have recently attracted great attention. Donoho's work established the signal recovery threshold using indicators such as restricted isotropy (RIP) and incoherence and proved that phase transition phenomena occur in compressed sampling. Nevertheless, the phase transition phenomenon of structured sparse signals remains unclear, and these studies mainly focused on simple sparse signals. Signals with a specific structure, such as the block or tree structures common in real-world applications, are called structured sparse signals. The objectives of this article are to study the phase transition phenomenon of structured sparse signals and to investigate how structured sparse signals affect the phase transition threshold. It begins with a summary of the common subspace of structured sparse signals and the theory of high-dimensional convex polytope random projections. Next, the strong threshold expression of block-structured and tree-structured sparse signals is derived after examining the weak and strong thresholds of structured sparse signals.