human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on the number of iterations for convergence of cosamp and sp algorithm"):
  Abstract: Compressive Sampling Matching Pursuit(CoSaMP) and Subspace Pursuit(SP) are popular compressive sensing greedy recovery algorithms. In this letter, we demonstrate that the CoSaMP algorithm can successfully reconstruct a $K$-sparse signal from a compressed measurement ${\bf y}={\bf A x}$ by a maximum of $5K$ iterations if the sensing matrix ${\bf A}$ satisfies the Restricted Isometry Constant (RIC) of $\delta_{4K} < \frac {1}{\sqrt{5}}$ and SP algorithm can reconstruct within $6K$ iteration when RIC of $\delta_{3K} < \frac {1}{\sqrt{5}}$ is satisfied. The proposed bound in convergence with respect to number of iterations shows improvement over the existing bounds for Subspace Pursuit and provides new results for CoSaMP.

Includes members:
  Member "improved analysis for subspace pursuit algorithm in terms of restricted isometry constant":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a new analysis for support recovery with block orthogonal matching pursuit")
  Member "oblique pursuits for compressed sensing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sparse signal recovery via generalized entropy functions minimization")
  Member "subspace pursuit for compressive sensing signal reconstruction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "compressive sensing for cut improvement and local clustering")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)