Results 1 to 10 of about 2,902 (117)

Low-Density Parity-Check Decoding Algorithm Based on Symmetric Alternating Direction Method of Multipliers [PDF]

open access: yesEntropy
The Alternating Direction Method of Multipliers (ADMM) has proven to be an efficient approach for implementing linear programming (LP) decoding of low-density parity-check (LDPC) codes.
Ji Zhang   +5 more
doaj   +2 more sources

A Dorsal Intramedullary T2‐Weighted Hypointense Signal Suggests Haemorrhagic Necrotic Material Indicating Ascending‐Descending Myelomalacia in Dogs [PDF]

open access: yesJournal of Veterinary Internal Medicine
Background Ascending‐descending myelomalacia (ADMM) is a progressive softening of the spinal cord observed in dogs after spinal cord injury (SCI).
Ursula Teubenbacher   +3 more
doaj   +2 more sources

Linearized ADMM for Nonconvex Nonsmooth Optimization With Convergence Analysis

open access: yesIEEE Access, 2019
Linearized alternating direction method of multipliers (ADMM) as an extension of ADMM has been widely used to solve linearly constrained problems in signal processing, machine learning, communications, and many other fields.
Xinyue Shen, Yuantao Gu
exaly   +3 more sources

A Weberized Total Variance Regularization-based Image Multiplicative Noise Model

open access: yesImage Analysis and Stereology, 2023
This paper considers Weber's law and proposes a new non-convex model for images contaminated by Gaussian noise and Rayleigh noise. The alternating direction method of multipliers (abbreviated as ADMM) is a recent popular method that can handle convex and
Xinyao Yu, Donghong Zhao
doaj   +1 more source

Modified ADMM algorithm for solving proximal bound formulation of multi-delay optimal control problem with bounded control [PDF]

open access: yesIranian Journal of Numerical Analysis and Optimization, 2022
This study presents an algorithm for solving optimal control problems with the objective function of the Lagrange-type and multiple delays on both the state and control variables of the constraints, with bounds on the control variable.
K.A. Dawodu
doaj   +1 more source

3D Capsule Networks for Object Classification With Weight Pruning

open access: yesIEEE Access, 2020
The proliferation of 3D sensors, due to the increased demand for 3D data, induced the 3D computer vision research in the last decade, and 3D data processing has gained a lot of interest.
Burak Kakillioglu   +3 more
doaj   +1 more source

Distributed optimal dispatching of the integrated electricity and natural gas systems considering spatial-temporal correlation of wind power

open access: yesZhejiang dianli, 2023
The fluctuation and intermittency of wind power have brought about unexpected problems to the optimal operation of the integrated electricity and natural gas systems. Furthermore, it makes the operation management of the integrated system more difficult.
XU Wenbin   +4 more
doaj   +1 more source

Accelerated convergence of time‐splitting algorithm by relaxation method

open access: yesIET Control Theory & Applications, 2022
The alternating direction method of multipliers (ADMM) is a widely used model predictive control (MPC) acceleration method. It adopts the time‐splitting technique, splitting the original problem into independent subproblems.
Jiaxin Gao   +6 more
doaj   +1 more source

Distributed online assignment of charging stations in persistent coverage control tasks based on LP relaxation and ADMM

open access: yesSICE Journal of Control, Measurement, and System Integration, 2022
This paper investigates distributed online assignment of charging stations for a drone network in a persistent coverage control task. To ensure persistency not only in motion but also in energy, drones need to go back to charging stations before running ...
Zhiyuan Lu   +3 more
doaj   +1 more source

ADMM-Based Differential Privacy Learning for Penalized Quantile Regression on Distributed Functional Data

open access: yesMathematics, 2022
Alternating Direction Method of Multipliers (ADMM) is a widely used machine learning tool in distributed environments. In the paper, we propose an ADMM-based differential privacy learning algorithm (FDP-ADMM) on penalized quantile regression for ...
Xingcai Zhou, Yu Xiang
doaj   +1 more source

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