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 "chaotic analog to information conversion with chaotic state modulation"):
  Abstract: Chaotic compressive sensing is a nonlinear framework for compressive sensing. Along the framework, this paper proposes a chaotic analog-to-information converter, chaotic modulation, to acquire and reconstruct band-limited sparse analog signals at sub-Nyquist rate. In the chaotic modulation, the sparse signal is randomized through state modulation of continuous-time chaotic system and one state output is sampled as compressive measurements. The reconstruction is achieved through the estimation of the sparse coefficients with principle of chaotic impulsive synchronization and Lp-norm regularized nonlinear least squares. The concept of supreme local Lyapunov exponents (SLLE) is introduced to study the reconstructablity. It is found that the sparse signals are reconstructable, if the largest SLLE of the error dynamical system is negative. As examples, the Lorenz system and Liu system excited by the sparse multi-tone signals are taken to illustrate the principle and the performance.

Includes members:
  Member "a compressed sensing framework of frequency sparse signals through chaotic system":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "chaotic analog to information conversion principle and reconstructability with parameter identifiability")
  Member "compressed sensing with nonlinear observations and related nonlinear optimisation problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recursive recovery of sparse signal sequences from compressive measurements a review")
  Member "sparse recovery from nonlinear measurements with applications in bad data detection for power networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "outlier robust extreme learning machine for multi target regression")
  Member "segmented compressed sampling for analog to information conversion method and performance analysis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gridless quadrature compressive sampling with interpolated array technique")
  Member "beyond nyquist efficient sampling of sparse bandlimited signals":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "secure and efficient compressed sensing based encryption with sparse matrices")
  Member "from theory to practice sub nyquist sampling of sparse wideband analog signals":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "image guided depth sampling and reconstruction")

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)