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: "nonlinear frequency division multiplexing"
  Abstract: Two signal multiplexing strategies for multi-user optical fiber communication are considered: Wavelength-division multiplexing (WDM) and nonlinear frequency-division multiplexing (NFDM), based on the nonlinear Fourier transform (NFT). The inverse NFT is implemented using an approach that is dual of the forward NFT and does not require solving integral equations. In contrast to prior work where NFDM is applied to single-user channels or combined with WDM, in this paper users' signals are multiplexed in the nonlinear Fourier domain. Furthermore, each user now sends a sequence of symbols. NFDM orthogonalizes the nonlinear Schr\"odinger equation in a generalized frequency and a generalized time. Thus all degrees-of-freedom are (deterministically) independent. A data rate of 10.5 bits per complex degree-of-freedom is achieved in a 15-user NFDM with $60$ GHz overall bandwidth at average input power $\mathcal P=-0.33$ dBm. Data rate in a comparable 15-user WDM with the same bandwidth and power is 5.26 bits per complex degree-of-freedom. The ratio of the spectral efficiency of NFDM and WDM is 2.23, taking into account bandwidth and time duration of signals at channel input and output. Thus, as a result of nonlinear multiplexing of users' signals, an NFDM spectral efficiency higher than the corresponding WDM spectral efficiency is demonstrated at high input power.

Connected through hyperedge HE-1 (induced by source paper "nonlinear fourier transform of truncated multi soliton pulses"):
  with members:
    - "why noise and dispersion may seriously hamper nonlinear frequency division multiplexing"
    - "probabilistic eigenvalue shaping for nonlinear fourier transform transmission"
    - "capacity lower bounds of the noncentral chi channel with applications to soliton amplitude modulation"
    - "demonstration of fully nonlinear spectrum modulated system in the highly nonlinear optical transmission regime"
    - "fast numerical nonlinear fourier transforms"

Connected through hyperedge HE-2 (induced by source paper "the kolmogorov zakharov model for optical fiber communication"):
  with members:
    - "linear and nonlinear frequency division multiplexing"
    - "information transmission using the nonlinear fourier transform part ii numerical methods"
    - "information transmission using the nonlinear fourier transform part i mathematical tools"

Connected through hyperedge HE-3 (induced by source paper "capacity lower bounds of the noncentral chi channel with applications to soliton amplitude modulation"):
  with members:
    - "performance prediction of nonbinary forward error correction in optical transmission experiments"
    - "nonlinear frequency division multiplexing in the focusing regime"
    - "a lower bound on the per soliton capacity of the nonlinear optical fibre channel"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "fast numerical nonlinear fourier transforms"
    - "upper bound on the capacity of the nonlinear schr odinger channel"
    - "information transmission using the nonlinear fourier transform part ii numerical methods"
    - "information transmission using the nonlinear fourier transform part i mathematical tools"

Connected through hyperedge HE-4 (induced by source paper "the asymptotic capacity of the optical fiber"):
  with members:
    - "models and information rates for multiuser optical fiber channels with nonlinearity and dispersion"
    - "conditions for a monotonic channel capacity"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "upper bound on the capacity of the nonlinear schr odinger channel"
    - "information transmission using the nonlinear fourier transform part ii numerical methods"
    - "information transmission using the nonlinear fourier transform part i mathematical tools"
    - "information transmission using the nonlinear fourier transform part iii spectrum modulation"
    - "transmission of information via the non linear scroedinger equation the random gaussian input case"

Connected through hyperedge HE-5 (induced by source paper "fast inverse nonlinear fourier transforms for continuous spectra of zakharov shabat type"):
  with members:
    - "digital backpropagation in the nonlinear fourier domain"
    - "fast numerical nonlinear fourier transforms"

Connected through hyperedge HE-6 (induced by source paper "nonlinear frequency division multiplexing in the focusing regime"):
  with members:
    - "digital backpropagation in the nonlinear fourier domain"

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)