Convergence of Stochastic Consensus Algorithms over Switching Noisy Networks

Seminar/Forum

Convergence of Stochastic Consensus Algorithms over Switching Noisy Networks

Richard Newton Rooms, Level 5
Electrical and Electronic Engineering Building, Building No. 193

Booking not required

Further Details

T: (03) 8344 6690

greteln@unimelb.edu.au

Associate Professor Minyi Huang will be presenting a seminar as part of the Control and Signal Processing Lab seminar series in the Department of Electrical & Electronic Engineering.

Associate Professor Huang's work considers consensus problems with delayed noisy measurements in switching networks and stochastic approximation algorithms with decreasing step sizes applied. Since the averaging weights must be selected in a distributed manner, the double stochasticity condition widely used in the literature does not hold in general and so the Lyapunov function based approach is difficult to apply. His work develops a new approach to prove consensus, which is achieved by establishing ergodic theorems for degenerating stochastic matrices.

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