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: "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
  Abstract: In this paper, we propose a distributed multiobject tracking algorithm through the use of multi-Bernoulli (MB) filter based on generalized covariance intersection (G-CI). Our analyses show that the G-CI fusion with two MB posterior distributions does not admit an accurate closed-form expression. To solve this problem, we first approximate the fused posterior as the unlabeled version of   $\delta$   -generalized labeled MB distribution, referred to as generalized MB (GMB) distribution. Then, to allow the subsequent fusion with another MB posterior distribution, e.g., fusion with a third sensor node in the sensor network, or fusion in the feedback working mode, we further approximate the fused GMB posterior distribution as an MB distribution which matches its first-order statistical moment. The proposed fusion algorithm is implemented using sequential Monte Carlo technique and its performance is highlighted by numerical results.

Connected through hyperedge HE-1 (induced by source paper "decentralized poisson multi bernoulli filtering for vehicle tracking"):
  with members:
    - "poisson multi bernoulli mixture filter direct derivation and implementation"
    - "mono camera 3d multi object tracking using deep learning detections and pmbm filtering"
    - "robust distributed fusion with labeled random finite sets"
    - "generalized optimal sub pattern assignment metric"
    - "multisensor poisson multi bernoulli filter for joint target sensor state tracking"
    - "extended object tracking introduction overview and applications"
    - "a metric on the space of finite sets of trajectories for evaluation of multi target tracking algorithms"
    - "marginal multi bernoulli filters rfs derivation of mht jipda and association based member"

Connected through hyperedge HE-2 (induced by source paper "multiobject fusion with minimum information loss"):
  with members:
    - "partial consensus and conservative fusion of gaussian mixtures for distributed phd fusion"
    - "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"
    - "the cauchy schwarz divergence for poisson point processes"
    - "consensus labeled random finite set filtering for distributed multi object tracking"

Connected through hyperedge HE-3 (induced by source paper "partial consensus and conservative fusion of gaussian mixtures for distributed phd fusion"):
  with members:
    - "robust distributed fusion with labeled random finite sets"
    - "distributed smc phd fusion for partial arithmetic average consensus"
    - "a scalable algorithm for tracking an unknown number of targets using multiple sensors"
    - "sigma point belief propagation"
    - "diffusion adaptation over networks"

Connected through hyperedge HE-4 (induced by source paper "second order statistics analysis and comparison between arithmetic and geometric average fusion application to multi sensor target tracking"):
  with members:
    - "partial consensus and conservative fusion of gaussian mixtures for distributed phd fusion"
    - "distributed smc phd fusion for partial arithmetic average consensus"
    - "a distributed particle phd filter with arithmetic average phd fusion"
    - "chernoff information of exponential families"
    - "gossip algorithms for distributed signal processing"

Connected through hyperedge HE-5 (induced by source paper "distributed joint sensor registration and multitarget tracking via sensor network"):
  with members:
    - "robust distributed fusion with labeled random finite sets"
    - "distributed on line multidimensional scaling for self localization in wireless sensor networks"
    - "simultaneous distributed sensor self localization and target tracking using belief propagation and likelihood consensus"
    - "distributed sensor localization in random environments using minimal number of anchor nodes"

Connected through hyperedge HE-6 (induced by source paper "multi sensor control for multi object bayes filters"):
  with members:
    - "multi bernoulli sensor control via minimization of expected estimation errors"
    - "sensor control for multi object tracking using labeled multi bernoulli filter"
    - "the cauchy schwarz divergence for poisson point processes"
    - "consensus labeled random finite set filtering for distributed multi object tracking"
    - "sensor management for multi target tracking via multi bernoulli filtering"
    - "on the finite time convergence of cyclic coordinate descent methods"

Connected through hyperedge HE-7 (induced by source paper "robust distributed fusion with labeled random finite sets"):
  with members:
    - "consensus labeled random finite set filtering for distributed multi object tracking"

Connected through hyperedge HE-8 (induced by source paper "statistical information fusion for multiple view sensor data in multi object tracking"):
  with members:
    - "multi bernoulli sensor control via minimization of expected estimation errors"
    - "the cauchy schwarz divergence for poisson point processes"
    - "sensor management for multi target tracking via multi bernoulli filtering"

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)