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: "fast inverse nonlinear fourier transforms for continuous spectra of zakharov shabat type"
  Abstract: The nonlinear Schr\"odinger equation (NSE) is well-known to model an ideal fiber-optic communication channel. Even though the NSE is a nonlinear evolution equation, it can be solved analytically using a nonlinear Fourier transform (NFT). Recently, there has been much interest in transceiver concepts that utilize this NFT and its inverse to (de-)modulate data. Fast algorithms for the (inverse) NFT are a key requirement for the simulation and real-time implementation of fiber-optic communication systems based on NFTs. While much progress has already been made for accelerating the forward NFT, less is known on its inverse. The nonlinear Fourier spectrum comprises a continuous and a discrete part in general, but so far only fast inverse NFTs for signals whose continuous spectrum is null have been reported in the literature. In this paper, we investigate the complementary case and propose the first fast inverse NFT for signals whose discrete spectrum is empty. This is the case required by transmitters in the recently proposed nonlinear inverse synthesis scheme, but the problem also occurs in different application areas such as fiber Bragg grating design. Our algorithms require only $\mathcal{O}(D\log^{2}D)$ floating point operations to generate $D$ samples of the desired signal, which is almost an order of magnitude faster than the current state of the art, $\mathcal{O}(D^{2})$. This paper also quantifies, apparently for the first time, the impact that truncating a signal in the time-domain has on the NFT.

Connected through hyperedge HE-1 (induced by source paper "time bandwidth product perspective for multi soliton phase modulation"):
  with members:
    - "correlated eigenvalues optical communications"
    - "probabilistic eigenvalue shaping for nonlinear fourier transform transmission"

Connected through hyperedge HE-2 (induced by source paper "linear and nonlinear frequency division multiplexing"):
  with members:
    - "a novel detection strategy for nonlinear frequency division multiplexing"
    - "decision feedback detection strategy for nonlinear frequency division multiplexing"
    - "communication using eigenvalues of higher multiplicity of the nonlinear fourier transform"
    - "the kolmogorov zakharov model for optical fiber communication"
    - "correlated eigenvalues optical communications"
    - "why noise and dispersion may seriously hamper nonlinear frequency division multiplexing"
    - "polarization division multiplexing based on the nonlinear fourier transform"
    - "nonlinear frequency division multiplexing in the focusing regime"

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)