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: "blind adaptive interference suppression based on set membership constrained constant modulus algorithms with dynamic bounds"
  Abstract: This work presents blind constrained constant modulus (CCM) adaptive algorithms based on the set-membership filtering (SMF) concept and incorporates dynamic bounds for interference suppression applications. We develop stochastic gradient and recursive least squares type algorithms based on the CCM design criterion in accordance with the specifications of the SMF concept. We also propose a blind framework that includes channel and amplitude estimators that take into account parameter estimation dependency, multiple access interference (MAI) and inter-symbol interference (ISI) to address the important issue of bound specification in multiuser communications. A convergence and tracking analysis of the proposed algorithms is carried out along with the development of analytical expressions to predict their performance. Simulations for a number of scenarios of interest with a DS-CDMA system show that the proposed algorithms outperform previously reported techniques with a smaller number of parameter updates and a reduced risk of overbounding or underbounding.

Connected through hyperedge HE-1 (induced by source paper "study of sparsity aware set membership adaptive algorithms with adjustable penalties"):
  with members:
    - "robust adaptive beamforming based on low rank and cross correlation techniques"
    - "adaptive reduced rank receive processing based on minimum symbol error rate criterion for large scale multiple antenna systems"
    - "robust adaptive beamforming using a low complexity shrinkage based mismatch estimation algorithm"

Connected through hyperedge HE-2 (induced by source paper "dynamic topology adaptation based on adaptive link selection algorithms for distributed estimation"):
  with members:
    - "robust adaptive beamforming using a low complexity shrinkage based mismatch estimation algorithm"
    - "performance limits for distributed estimation over lms adaptive networks"

Connected through hyperedge HE-3 (induced by source paper "multi user flexible coordinated beamforming using lattice reduction for massive mimo systems"):
  with members:
    - "robust adaptive beamforming using a low complexity shrinkage based mismatch estimation algorithm"
    - "multi branch tomlinson harashima precoding design for mu mimo systems theory and algorithms"
    - "generalized design of low complexity block diagonalization type precoding algorithms for multiuser mimo systems"
    - "reduced rank doa estimation based on joint iterative subspace optimization and grid search"
    - "massive mimo systems signal processing challenges and research trends"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "adaptive distributed space time coding based on adjustable code matrices for cooperative mimo relaying systems"
    - "adaptive reduced rank lcmv beamforming algorithms based on joint iterative optimization of filters design and analysis"

Connected through hyperedge HE-4 (induced by source paper "coordinate tomlinson harashima precoding design for overloaded multi user mimo systems"):
  with members:
    - "robust adaptive beamforming using a low complexity shrinkage based mismatch estimation algorithm"
    - "multi branch tomlinson harashima precoding design for mu mimo systems theory and algorithms"
    - "generalized design of low complexity block diagonalization type precoding algorithms for multiuser mimo systems"
    - "reduced rank doa estimation based on joint iterative subspace optimization and grid search"
    - "adaptive distributed space time coding based on adjustable code matrices for cooperative mimo relaying systems"
    - "adaptive reduced rank lcmv beamforming algorithms based on joint iterative optimization of filters design and analysis"
    - "lll reduction achieves the receive diversity in mimo decoding"

Connected through hyperedge HE-5 (induced by source paper "detection and estimation algorithms in massive mimo systems"):
  with members:
    - "scalable synchronization and reciprocity calibration for distributed multiuser mimo"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "adaptive distributed space time coding based on adjustable code matrices for cooperative mimo relaying systems"
    - "a new class of upper bounds on the log partition function"
    - "uplink comp under a constrained backhaul and imperfect channel knowledge"

Connected through hyperedge HE-6 (induced by source paper "distributed low rank estimation based on joint iterative optimization in wireless sensor networks"):
  with members:
    - "sparsity aware adaptive algorithms based on alternating optimization with shrinkage"
    - "single bit and reduced dimension diffusion strategies over distributed networks"
    - "mimo radar using compressive sampling"

Connected through hyperedge HE-7 (induced by source paper "set membership adaptive constant modulus algorithm with a generalized sidelobe canceler and dynamic bounds for beamforming"):
  with members:
    - "adaptive reduced rank lcmv beamforming algorithms based on joint iterative optimization of filters design and analysis"

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)