Generalizable preconditioning strategies for MAP PET reconstruction using Poisson likelihood. [PDF]
Colombo MN, Paganoni M, Presotto L.
europepmc +1 more source
Two-phase quasi-Newton method for unconstrained optimization problem [PDF]
Suvra Kanti Chakraborty +1 more
openalex +1 more source
AI‐enabled bumpless transfer control strategy for legged robot with hybrid energy storage system
Abstract Designing Hybrid energy storage system (HESS) for a legged robot is significant to improve the motion performance and energy efficiency of the robot. However, switching between the driving mode and regenerative braking mode in the HESS may generate a torque bump, which has brought significant challenges to the stability of the robot locomotion.
Zhiwu Huang +6 more
wiley +1 more source
Efficient optimization accelerator framework for multi-state spin Ising problems. [PDF]
Garg C, Salahuddin S.
europepmc +1 more source
Coevolutionary Neural Dynamics With Learnable Parameters for Nonconvex Optimisation
ABSTRACT Nonconvex optimisation plays a crucial role in science and industry. However, existing methods often encounter local optima or provide inferior solutions when solving nonconvex optimisation problems, lacking robustness in noise scenarios. To address these limitations, we aim to develop a robust, efficient and globally convergent solver for ...
Yipiao Chen +3 more
wiley +1 more source
Dynamic Hassan Nelder Mead with Simplex Free Selectivity for Unconstrained Optimization
Hassan Musafer, Ausif Mahmood
openalex +1 more source
Robotic Cell Micromanipulation Skill Learning via Imitation‐Enhanced Reinforcement Learning
ABSTRACT Humans can learn complex and dexterous manipulation tasks by observing videos, imitating and exploring. Multiple end‐effectors manipulation of free micron‐sized deformable cells is one of the challenging tasks in robotic micromanipulation. We propose an imitation‐enhanced reinforcement learning method inspired by the human learning process ...
Youchao Zhang +6 more
wiley +1 more source
Fixed‐Time Zeroing Neural Dynamics for Adaptive Coordination of Multi‐Agent Systems
ABSTRACT This paper presents an adaptive multi‐agent coordination (AMAC) strategy suitable for complex scenarios, which only requires information exchange between neighbouring robots. Unlike traditional multi‐agent coordination methods that are solved by neural dynamics, the proposed strategy displays greater flexibility, adaptability and scalability ...
Cheng Hua +3 more
wiley +1 more source
Adaptively coupled phase retrieval in multi‐peak Bragg coherent diffraction imaging
We present an adaptively coupled phase retrieval algorithm for multi‐peak Bragg coherent diffraction imaging. The technique uses the redundant information contained in separate Bragg peaks to detect and remove spurious signal.Recent advances in Bragg coherent diffraction imaging (BCDI) experimental techniques permit routine measurement of multiple ...
J. Nicholas Porter +12 more
wiley +1 more source

