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 "distributed low rank estimation based on joint iterative optimization in wireless sensor networks"):
  Abstract: This paper proposes a novel distributed reduced--rank scheme and an adaptive algorithm for distributed estimation in wireless sensor networks. The proposed distributed scheme is based on a transformation that performs dimensionality reduction at each agent of the network followed by a reduced-dimension parameter vector. A distributed reduced-rank joint iterative estimation algorithm is developed, which has the ability to achieve significantly reduced communication overhead and improved performance when compared with existing techniques. Simulation results illustrate the advantages of the proposed strategy in terms of convergence rate and mean square error performance.

Includes members:
  Member "sparsity aware adaptive algorithms based on alternating optimization with shrinkage":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "study of coarse quantization aware block diagonalization algorithms for mimo systems with low resolution")
  Member "single bit and reduced dimension diffusion strategies over distributed networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed low rank adaptive algorithms based on alternating optimization and applications")
  Member "blind adaptive interference suppression based on set membership constrained constant modulus algorithms with dynamic bounds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "study of sparsity aware set membership adaptive algorithms with adjustable penalties")
  Member "mimo radar using compressive sampling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sparse blind deconvolution for distributed radar autofocus imaging")

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)