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 "noise weighting in the design of delta sigma modulators with a psychoacoustic coder as an example"):
  Abstract: A design flow for ΔΣ modulators is illustrated, allowing quantization noise to be shaped according to an arbitrary weighting profile. Based on finite-impulse-response noise transfer functions, possibly with high order, the flow is best suited for digital architectures. This work builds on a recent proposal in which the modulator is matched to the reconstruction filter, showing that this type of optimization can benefit a wide range of applications in which noise (including in-band noise) is known to have a different impact at different frequencies. The designs of a multiband modulator, a modulator avoiding dc noise, and an audio modulator capable of distributing quantization artifacts according to a psychoacoustic model are discussed as examples. A software toolbox is provided as a general design aid and to replicate the proposed results.

Includes members:
  Member "output filter aware optimization of the noise shaping properties of δσ modulators via semi definite programming":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mean squared error analysis of quantizers with error feedback")
  Member "should δσ modulators used in ac motor drives be adapted to the mechanical load of the motor":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "output filter aware optimization of the noise shaping properties of δσ modulators via semi definite programming")
  Member "frequency domain min max optimization of noise shaping delta sigma modulators":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "min max design of feedback quantizers for netorwked control systems")

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)