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 "coded acquisition of high frame rate video"):
  Abstract: High frame rate video (HFV) is an important investigational tool in sciences, engineering, and military. In ultrahigh speed imaging, the obtainable temporal, spatial, and spectral resolutions are limited by the sustainable throughput of in-camera mass memory, lower bound of exposure time, and illumination conditions. To break these bottlenecks, we propose a new coded video acquisition framework that employs K ≥ 2 cameras, each of which makes random measurements of the video signal in both temporal and spatial domains. For each of the K cameras, this multicamera strategy greatly relaxes the stringent requirements in memory speed, shutter speed, and illumination strength. The recovery of HFV from these random measurements is posed and solved as a large-scale l#N# 1#N#minimization problem by exploiting joint temporal and spatial sparsities of the 3D signal. Three coded video acquisition techniques of varied tradeoffs between performance and hardware complexity are developed: framewise coded acquisition; pixelwise coded acquisition; and columnwise-rowwise coded acquisition. The performances of these techniques are analyzed in relation to the sparsity of the underlying video signal. Simulations of these new HFV capture techniques are carried out and experimental results are reported.

Includes members:
  Member "the restricted isometry property for random block diagonal matrices":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sampling of graph signals via randomized local aggregations")
  Member "note on rip based co sparse analysis":
    also connected through other hyperedges:
      (none)

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.MM(Multimedia)