Distributed Fast-Tracking Alternating Direction Method of Multipliers (ADMM) Algorithm with Optimal Convergence Rate

2021 ◽  
Author(s):  
Shreyansh Shethia ◽  
Akshita Gupta ◽  
Omanshu Thapliyal ◽  
Inseok Hwang
Keyword(s):  
Convergence Rate ◽  
Alternating Direction Method ◽  
Method Of Multipliers ◽  
Optimal Convergence Rate ◽  
Optimal Convergence ◽  
Fast Tracking ◽  
Alternating Direction ◽  
Admm Algorithm

Image denoising algorithm of compressed sensing based on alternating direction method of multipliers

2021 ◽  
pp. 2250009
Author(s):  
Changjie Fang ◽  
Jingyu Chen ◽  
Shenglan Chen
Keyword(s):  
Compressed Sensing ◽  
Convergence Rate ◽  
Objective Function ◽  
Image Denoising ◽  
Alternating Direction Method ◽  
Method Of Multipliers ◽  
Alternating Direction ◽  
Time Simulation ◽  
Optimal Value ◽  
Simulation Results

In this paper, we propose an image denoising algorithm for compressed sensing based on alternating direction method of multipliers (ADMM). We prove that the objective function of the iterates approaches the optimal value. We also prove the [Formula: see text] convergence rate of our algorithm in the ergodic sense. At the same time, simulation results show that our algorithm is more efficient in image denoising compared with existing methods.

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