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 "ir uwb detection and fusion strategies using multiple detector types"):
  Abstract: Optimal detection of ultra wideband (UWB) pulses in a UWB transceiver employing multiple detector types is proposed and analyzed in this paper. To enable the transceiver to be used for multiple applications, the designers have different types of detectors such as energy detector, amplitude detector, etc., built in to a single transceiver architecture. We propose several fusion techniques for fusing decisions made by individual IR-UWB detectors. In order to get early insight into theoretical achievable performance of these fusion techniques, we assess the performance of these fusion techniques for commonly used detector types like matched filter, energy detector and amplitude detector under Gaussian assumption. These are valid for ultra short distance communication and in UWB systems operating in millimeter wave (mmwave) band with high directivity gain. In this paper, we utilize the performance equations of different detectors, to device distinct fusion algorithms. We show that the performance can be improved approximately by 4 dB in terms of signal to noise ratio (SNR) for high probability of detection of a UWB signal (> 95%), by fusing decisions from multiple detector types compared to a standalone energy detector, in a practical scenario.

Includes members:
  Member "decision fusion with unknown sensor detection probability":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rician mimo channel and jamming aware decision fusion")
  Member "cooperative localization by dual foot mounted inertial sensors and inter agent ranging":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "range only collaborative localization for ground vehicles")

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)