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 "joint doa and frequency estimation with sub nyquist sampling in the sparse array system"):
  Abstract: Several array systems along with algorithms based on sub-Nyquist sampling techniques have been extensively studied. This letter is committed to the joint frequency and direction-of-arrival estimation of more sources than sensors in a subband by using sparse arrays with sub-Nyquist sampling. The newly defined block vectorization eliminates the interference from sub-Nyquist sampling. Based on this, a novel augmented sample covariance matrix method is proposed, which enhances the spatial degrees of freedom and increases the number of identifiable sources. Simulations show that the joint estimation can be realized at a lower sampling rate with fewer sensors at the expense of a degradation in estimation performance. Such an algorithm provides a tradeoff between the expensive resource of sensors and channels, and the estimation performance.

Includes members:
  Member "joint doa and frequency estimation with sub nyquist sampling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a simplified sub nyquist receiver architecture for joint doa and frequency estimation")
  Member "wideband spectrum sensing for cognitive radio networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "20 years of evolution from cognitive to intelligent communications")

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)