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 "component based modeling and processing of medical ultrasound signals"):
  Abstract: Component-based modeling and processing can be found in many signal and image processing applications. In this paper, we apply this approach to cardiac medical ultrasound imaging. We show how the raw data generated in the ultrasound scanning process can be modeled as consisting of two distinct components. By decomposing these signals into the two components, we are able to apply separate processing pipelines tailored to each component. The potential benefits of this approach to medical ultrasound imaging are demonstrated in two central issues of the commonly used processing: 1) the very large amounts of data generated by the scanning process, and 2) artifacts in the images and videos generated by standard processing, commonly referred to as side lobe artifacts. We manage to compress the data by a factor of over 20 as well as remove the side lobe artifacts. These benefits are demonstrated on both simulated data and real cardiac scanning data.

Includes members:
  Member "innovation rate sampling of pulse streams with application to ultrasound imaging":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sampling and super resolution of sparse signals beyond the fourier domain")
  Member "compressed beamforming applied to b mode ultrasound imaging":
    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.IT(Information Theory)