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 "partial consensus and conservative fusion of gaussian mixtures for distributed phd fusion"):
  Abstract: We propose a novel consensus notion, called “partial consensus,” for distributed Gaussian mixture probability hypothesis density fusion based on a decentralized sensor network, in which only highly weighted Gaussian components (GCs) are exchanged and fused across neighbor sensors. It is shown that this not only gains high efficiency in both network communication and fusion computation, but also significantly compensates the effects of clutter and missed detections. Two “conservative” mixture reduction schemes are devised for refining the combined GCs. One is given by pairwise averaging GCs between sensors based on Hungarian assignment and the other merges close GCs for trace minimal, yet, conservative covariance. The close connection of the result to the two approaches, known as covariance union and arithmetic averaging, is unveiled. Simulations based on a sensor network consisting of both linear and nonlinear sensors, have demonstrated the advantage of our approaches over the generalized covariance intersection approach.

Includes members:
  Member "robust distributed fusion with labeled random finite sets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "decentralized poisson multi bernoulli filtering for vehicle tracking")
  Member "distributed smc phd fusion for partial arithmetic average consensus":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multiobject fusion with minimum information loss")
  Member "a scalable algorithm for tracking an unknown number of targets using multiple sensors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic radar network of uavs a joint navigation and tracking approach")
  Member "distributed fusion with multi bernoulli filter based on generalized covariance intersection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "decentralized poisson multi bernoulli filtering for vehicle tracking")
  Member "sigma point belief propagation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "peregrine network localization and navigation with scalable inference and efficient operation")
  Member "diffusion adaptation over networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sparsity constrained distributed unmixing of hyperspectral data")

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.SY(Systems and Control)