Dynamical Sparse Signal Recovery with Fixed-Time Convergence

Junying Ren (1) , Lei Yu (1) , Chengcheng Lyu (1) , Gang Zheng (2, 3) , Hong Sun (4) , Jean-Pierre Barbot (5)

1 Wuhan University [China]
2 DEFROST - Deformable Robots Simulation Team
3 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
4 School of Electronic Information [Wuhan]
5 QUARTZ - Laboratoire QUARTZ

Arising in a large number of application areas, sparse recovery (SR) has been exhaustively investigated and many algorithms have been proposed. Different from the numerical methods realized by iterative algorithm, the recent continuous approach is realized through analog circuit, which takes advantage of short time-delay and fast convergence faster. However, the existing continuous method for SR still has the space to further improve the convergence speed. Consequently, in this paper, we propose a new dy-namical continuous system to solve the sparse signal recovery problem with fixed-time convergence property.

Mots clés: Sparse Recovery; Dynamical System; Fixed-Time Convergence

Domaines: Traitement du signal et de l'image [eess.SP]

Junying Ren, Lei Yu, Chengcheng Lyu, Gang Zheng, Hong Sun, et al.. Dynamical Sparse Signal Recovery with Fixed-Time Convergence. Signal Processing, 2019, 162, pp.65-74. ⟨10.1016/j.sigpro.2019.04.010⟩. ⟨hal-02406715⟩