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: "analysis of decimation on finite frames with sigma delta quantization"
  Abstract: In Analog-to-digital (A/D) conversion on oversampled bandlimited functions, integration of samples in blocks before down-sampling, known as decimation, has been proven to greatly improve the efficiency of data storage while maintaining high accuracy. In particular, when coupled with the $\Sigma\Delta$ quantization scheme, the reconstruction error decays exponentially with respect to the bit-rate. Here, a similar result is proved for finite unitarily generated frames. Specifically, under certain constraints on the generator, decimation merely increases the reconstruction error estimate by a factor of $\pi/2$, independent of the block size. On the other hand, efficient encodings of samples are made possible from decimation, and thus the error decays exponentially with respect to total bits used for data storage. Moreover, the decimation on finite frames has the multiplicative structure that allows the process to be broken down into successive iterations of decimation with smaller blocks, which opens up the possibility for parallel computation and signal transmission through multiple nodes.

Connected through hyperedge HE-1 (induced by source paper "adapted decimation on finite frames for arbitrary orders of sigma delta quantization"):
  with members:
    - "fast binary embeddings and quantized compressed sensing with structured matrices"
    - "distributed noise shaping quantization i beta duals of finite frames and near optimal quantization of random measurements"
    - "exact reconstruction of signals in evolutionary systems via spatiotemporal trade off"
    - "a deterministic analysis of decimation for sigma delta quantization of bandlimited functions"
    - "noise shaping quantization methods for frame based and compressive sampling systems"
    - "near optimal encoding for sigma delta quantization of finite frame expansions"

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)