human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "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.

Connected through hyperedge HE-1 (induced by source paper "multiobject fusion with minimum information loss"):
  with members:
    - "second order statistics analysis and comparison between arithmetic and geometric average fusion application to multi sensor target tracking"
    - "robust distributed fusion with labeled random finite sets"
    - "distributed smc phd fusion for partial arithmetic average consensus"
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "the cauchy schwarz divergence for poisson point processes"
    - "consensus labeled random finite set filtering for distributed multi object tracking"

Connected through hyperedge HE-2 (induced by source paper "second order statistics analysis and comparison between arithmetic and geometric average fusion application to multi sensor target tracking"):
  with members:
    - "distributed smc phd fusion for partial arithmetic average consensus"
    - "a distributed particle phd filter with arithmetic average phd fusion"
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "chernoff information of exponential families"
    - "gossip algorithms for distributed signal processing"

Connected through hyperedge HE-3 (induced by source paper "distributed smc phd fusion for partial arithmetic average consensus"):
  with members:
    - "a scalable algorithm for tracking an unknown number of targets using multiple sensors"
    - "distributed bayesian filtering using logarithmic opinion pool for dynamic sensor networks"
    - "the cauchy schwarz divergence for poisson point processes"

Question: Please tell me which class the center node 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)