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 "design and analysis of distributed state estimation algorithms based on belief propagation and applications in smart grids"):
  Abstract: We present a detailed study on application of factor graphs and the belief propagation (BP) algorithm to the power system state estimation (SE) problem. We start from the BP solution for the linear DC model, for which we provide a detailed convergence analysis. Using BP-based DC model we propose a fast real-time state estimator for the power system SE. The proposed estimator is easy to distribute and parallelize, thus alleviating computational limitations and allowing for processing measurements in real time. The presented algorithm may run as a continuous process. #R##N#Using insights from the DC model, we use two different approaches to derive the BP algorithm for the non-linear model. The first method directly applies BP methodology, however, providing only approximate BP solution for the non-linear model. In the second approach, we make a key further step by providing the solution in which the BP is applied sequentially over the non-linear model, akin to what is done by the Gauss-Newton method. The resulting iterative Gauss-Newton belief propagation (GN-BP) algorithm can be interpreted as a distributed Gauss-Newton method with the same accuracy as the centralized SE.

Includes members:
  Member "linear state estimation via 5g c ran cellular networks using gaussian belief propagation":
    also connected through other hyperedges:
      (none)
  Member "fast real time dc state estimation in electric power systems using belief propagation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed gauss newton method for ac state estimation using belief propagation")
  Member "distributed gauss newton method for ac state estimation a belief propagation approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fast real time dc state estimation in electric power systems using belief propagation")
  Member "distributed hybrid power state estimation under pmu sampling phase errors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rf based energy harvesting in decode and forward relaying systems ergodic and outage capacities")
  Member "state estimation in electric power systems using belief propagation an extended dc model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed gauss newton method for ac state estimation a belief propagation approach")
  Member "scalable uplink signal detection in c rans via randomized gaussian message passing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cnn based signal detection for banded linear systems")

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)