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 "photoplethysmography based heart rate monitoring in physical activities via joint sparse spectrum reconstruction"):
  Abstract: Goal:  A new method for heart rate monitoring using photoplethysmography (PPG) during physical activities is proposed.  Methods : It jointly estimates the spectra of PPG signals and simultaneous acceleration signals, utilizing the multiple measurement vector model in sparse signal recovery. Due to a common sparsity constraint on spectral coefficients, the method can easily identify and remove the spectral peaks of motion artifact (MA) in the PPG spectra. Thus, it does not need any extra signal processing modular to remove MA as in some other algorithms. Furthermore, seeking spectral peaks associated with heart rate is simplified.  Results  : Experimental results on 12 PPG datasets sampled at 25 Hz and recorded during subjects’ fast running showed that it had high performance. The average absolute estimation error was 1.28 beat/min and the standard deviation was 2.61 beat/min.  Conclusion and Significance : These results show that the method has great potential to be used for PPG-based heart rate monitoring in wearable devices for fitness tracking and health monitoring.

Includes members:
  Member "troika a general framework for heart rate monitoring using wrist type photoplethysmographic signals during intensive physical exercise":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an affective situation labeling system from psychological behaviors in emotion recognition")
  Member "spatiotemporal sparse bayesian learning with applications to compressed sensing of multichannel physiological signals":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rectified gaussian scale mixtures and the sparse non negative least squares problem")
  Member "joint sparsity recovery for spectral compressed sensing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "super resolution blind channel and signal estimation for massive mimo with one dimensional antenna array")
  Member "support recovery of sparse signals in the presence of multiple measurement vectors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint sparse recovery using signal space matching pursuit")
  Member "average case analysis of multichannel sparse recovery using convex relaxation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sample measurement tradeoff in support recovery under a subgaussian prior")

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.OH(Other Computer Science)