Choice of step-size for consensus protocol in changing conditions via stochastic approximation type algorithm

2016 ◽  
Author(s):  
Konstantin Amelin ◽  
Natalia Amelina ◽  
Yury Ivanskiy ◽  
Yuming Jiang
Keyword(s):  
Stochastic Approximation ◽  
Consensus Protocol ◽  
Step Size ◽  
Type Algorithm ◽  
Approximation Type

scholarly journals Analyzing the (1, λ) Evolution Strategy via Stochastic Approximation Methods

1995 ◽  
Vol 3 (4) ◽  
pp. 473-489 ◽  
Author(s):  
G. Yin ◽  
G. Rudolph ◽  
H.-P, Schwefel
Keyword(s):  
Dynamical Systems ◽  
Stochastic Approximation ◽  
Error Bounds ◽  
Continuous Time ◽  
Estimation Error ◽  
Evolution Strategy ◽  
Approximation Methods ◽  
Step Size ◽  
Approximation Type

The main objective of this paper is to analyze the (1, λ) evolution strategy by use of stochastic approximation methods. Both constant and decreasing step size algorithms are studied. Convergence and estimation error bounds for the (1, λ) evolution strategy are developed. First the algorithm is converted to a recursively defined scheme of stochastic approximation type. Then the analysis is carried out by using the analytic tools from stochastic approximation. In lieu of examining the discrete iterates, suitably scaled sequences are defined. These interpolated sequences are then studied in detail. It is shown that the limits of the sequences have natural connections to certain continuous time dynamical systems.

Stochastic Approximation Type Nonlinear Filter with Randomly Varying Truncations

2000 ◽  
Vol 33 (15) ◽  
pp. 1145-1150 ◽  
Author(s):  
Katsuji Uosaki ◽  
Han-Fu Chen ◽  
Toshiharu Hatanaka
Keyword(s):  
Stochastic Approximation ◽  
Nonlinear Filter ◽  
Approximation Type
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