human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "complex valued random vectors and channels entropy divergence and capacity"
  Abstract: Recent research has demonstrated significant achievable performance gains by exploiting circularity/noncircularity or properness/improperness of complex-valued signals. In this paper, we investigate the influence of these properties on important information theoretic quantities such as entropy, divergence, and capacity. We prove two maximum entropy theorems that strengthen previously known results. The proof of the first maximum entropy theorem is based on the so-called circular analog of a given complex-valued random vector. The introduction of the circular analog is additionally supported by a characterization theorem that employs a minimum Kullback-Leibler divergence criterion. In the proof of the second maximum entropy theorem, results about the second-order structure of complex-valued random vectors are exploited. Furthermore, we address the capacity of multiple-input multiple-output (MIMO) channels. Regardless of the specific distribution of the channel parameters (noise vector and channel matrix, if modeled as random), we show that the capacity-achieving input vector is circular for a broad range of MIMO channels (including coherent and noncoherent scenarios). Finally, we investigate the situation of an improper and Gaussian distributed noise vector. We compute both capacity and capacity-achieving input vector and show that improperness increases capacity, provided that the complementary covariance matrix is exploited. Otherwise, a capacity loss occurs, for which we derive an explicit expression.

Connected through hyperedge HE-1 (induced by source paper "rate region boundary of the siso z interference channel with improper signaling"):
  with members:
    - "benefits of improper signaling for underlay cognitive radio"
    - "improper signaling for symbol error rate minimization in k user interference channel"
    - "joint transmitter and receiver optimization for improper complex second order stationary data sequence"
    - "optimized transmission with improper gaussian signaling in the k user miso interference channel"
    - "transmit optimization with improper gaussian signaling for interference channels"
    - "interference alignment with asymmetric complex signaling settling the host madsen nosratinia conjecture"

Connected through hyperedge HE-2 (induced by source paper "optimum co design for spectrum sharing between matrix completion based mimo radars and a mimo communication system"):
  with members:
    - "mimo mc radar a mimo radar approach based on matrix completion"
    - "overlapped mimo radar waveform design for coexistence with communication systems"
    - "spatial compressive sensing for mimo radar"
    - "matrix completion in colocated mimo radar recoverability bounds theoretical guarantees"
    - "target estimation in colocated mimo radar via matrix completion"
    - "mimo radar using compressive sampling"
    - "dynamic resource allocation in cognitive radio networks"
    - "matrix completion with noise"

Connected through hyperedge HE-3 (induced by source paper "proper complex gaussian processes for regression"):
  with members:
    - "gaussian processes for nonlinear signal processing an overview of recent advances"
    - "the augmented complex kernel lms"
    - "extension of wirtinger s calculus to reproducing kernel hilbert spaces and the complex kernel lms"

Connected through hyperedge HE-4 (induced by source paper "transmit optimization with improper gaussian signaling for interference channels"):
  with members:
    - "robust monotonic optimization framework for multicell miso systems"
    - "achieving global optimality for weighted sum rate maximization in the k user gaussian interference channel with multiple antennas"
    - "optimal beamforming in interference networks with perfect local channel information"
    - "cooperative algorithms for mimo interference channels"
    - "on feasibility of interference alignment in mimo interference networks"
    - "cooperative interference management with miso beamforming"
    - "linear transceiver design for interference alignment complexity and computation"
    - "on feasibility of interference alignment in mimo interference networks"

Connected through hyperedge HE-5 (induced by source paper "improving achievable rate for the two user siso interference channel with improper gaussian signaling"):
  with members:
    - "cooperative interference management with miso beamforming"
    - "interference alignment with asymmetric complex signaling settling the host madsen nosratinia conjecture"
    - "gaussian interference channel capacity to within one bit"

Question: Please tell me which class the center node 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)