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 "trigonometric dictionary based codec for music compression with high quality recovery"):
  Abstract: A codec for compression of music signals is proposed. The method belongs to the class of transform lossy compression. It is conceived to be applied in the high quality recovery range though. The transformation, endowing the codec with its distinctive feature, relies on the ability to construct high quality sparse approximation of music signals. This is achieved by a redundant trigonometric dictionary and a dedicated pursuit strategy. The potential of the approach is illustrated by comparison with the OGG Vorbis format, on a sample consisting of clips of melodic music. The comparison evidences remarkable improvements in compression performance for the identical quality of the decompressed signal.

Includes members:
  Member "cooperative greedy pursuit strategies for sparse signal representation by partitioning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analysis of a low memory implementation of the orthogonal matching pursuit greedy strategy")
  Member "hierarchized block wise image approximation by greedy pursuit strategies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analysis of a low memory implementation of the orthogonal matching pursuit greedy strategy")

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.SD(Sound)