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 "mse estimates for multitaper spectral estimation and off grid compressive sensing"):
  Abstract: We obtain estimates for the Mean Squared Error (MSE) for the multitaper spectral estimator and certain compressive acquisition methods for multi-band signals. We confirm a fact discovered by Thomson [Spectrum estimation and harmonic analysis, Proc. IEEE, 1982]: assuming bandwidth $W$ and $N$ time domain observations, the average of the square of the first $K=2NW$ Slepian functions approaches, as $K$ grows, an ideal band-pass kernel for the interval $[-W,W]$. We provide an analytic proof of this fact and measure the corresponding rate of convergence in the $L^{1}$ norm. This validates a heuristic approximation used to control the MSE of the multitaper estimator. The estimates have also consequences for the method of compressive acquisition of multi-band signals introduced by Davenport and Wakin, giving MSE approximation bounds for the dictionary formed by modulation of the critical number of prolates.

Includes members:
  Member "time frequency and time scale analysis of deformed stationary processes with application to non stationary sound modeling":
    also connected through other hyperedges:
      (none)
  Member "approximating sampled sinusoids and multiband signals using multiband modulated dpss dictionaries":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressed sensing with probability based prior information")
  Member "fourier bessel rotational invariant eigenimages":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cryo electron microscopy image analysis using multi frequency vector diffusion maps")
  Member "compressive sensing of analog signals using discrete prolate spheroidal sequences":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a universal sampling method for reconstructing signals with simple fourier transforms")

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)