Reaching consensus via polynomial stochastic operators: A general study

DOI10.1007/978-981-10-6409-8_14zbMath1380.93236OpenAlexW2769141584MaRDI QIDQ1696873

Khikmat Saburov, Mansoor Saburov

Publication date: 15 February 2018

Full work available at URL: https://doi.org/10.1007/978-981-10-6409-8_14

zbMATH Keywords

consensusKrause mean processMarkov chain with memorypolynomial stochastic operatorsstochastic hypermatrices

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Decentralized systems (93A14) Stochastic systems in control theory (general) (93E03) Stochastic matrices (15B51)

Related Items (8)

Ergodicity of non-homogeneous \(\mathbf{p}\)-majorizing quadratic stochastic operators ⋮ Krause mean processes generated by cubic stochastic diagonally primitive matrices ⋮ Krause mean processes generated by cubic stochastic matrices IV: off-diagonally uniformly positive nonautonomous cubic stochastic matrices ⋮ Applications of quadratic stochastic operators to nonlinear consensus problems ⋮ Ganikhodjaev's conjecture on mean ergodicity of quadratic stochastic operators ⋮ Reaching a consensus via Krause mean processes in multi-agent systems: quadratic stochastic operators ⋮ Iterated means dichotomy for discrete dynamical systems ⋮ Ergodicity of $p$-majorizing nonlinear Markov operators on the finite dimensional space

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