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: "capacity analysis for continuous alphabet channels with side information part i a general framework"
  Abstract: Capacity analysis for channels with side information at the receiver has been an active area of interest. This problem is well investigated for the case of finite-alphabet channels. However, the results are not easily generalizable to the case of continuous-alphabet channels due to analytical difficulties inherent with continuous alphabets. In the first part of this two-part paper, we address an analytical framework for capacity analysis of continuous alphabet channels with side information at the receiver. For this purpose, we establish novel necessary and sufficient conditions for weak* continuity and strict concavity of the mutual information. These conditions are used in investigating the existence and uniqueness of the capacity-achieving measures. Furthermore, we derive necessary and sufficient conditions that characterize the capacity value and the capacity-achieving measure for continuous-alphabet channels with side information at the receiver.

Connected through hyperedge HE-1 (induced by source paper "directed information on abstract spaces properties and variational equalities"):
  with members:
    - "sequential necessary and sufficient conditions for capacity achieving distributions of channels with memory and feedback"
    - "capacity achieving distributions information lossless randomized strategies for feedback channels with memory the lqg theory of directed information part ii"
    - "optimal nonanticipative estimation schemes for time varying gauss markov processes"
    - "capacity of binary state symmetric channel with and without feedback and transmission cost"
    - "information nonanticipative rate distortion function and its applications"
    - "information structures for feedback capacity of channels with memory and transmission cost stochastic optimal control variational equalities part i"
    - "nonanticipative rate distortion function and relations to filtering theory"
    - "capacity of a post channel with and without feedback"

Connected through hyperedge HE-2 (induced by source paper "directed information on abstract spaces properties and extremum problems"):
  with members:
    - "nonanticipative rate distortion function and relations to filtering theory"
    - "directed information on abstract spaces properties and variational equalities"
    - "causal rate distortion function on abstract alphabets optimal reconstruction and properties"
    - "causal rate distortion function on abstract alphabets and optimal reconstruction kernel"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-3 (induced by source paper "on the boundedness of the support of optimal input measures for rayleigh fading channels"):
  with members:
    - "capacity analysis for continuous alphabet channels with side information part ii mimo channels"

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.IT(Information Theory)