Results 111 to 120 of about 1,099,998 (291)

QNOMP: A Quasi-Newton-Based Joint Multipath Optimization Method for Super-Resolution Channel Estimation and Extrapolation

IEEE Access
Channel estimation and extrapolation are key challenges in massive multiple-input multiple-output communications. In this paper, we propose a quasi-Newton-based joint multipath optimization approach called Quasi-Newton Orthogonal Matching Pursuit (QNOMP)
Yi Zeng, Mingguang Han, Xiaoguang Li, Tiejun Li   +3 more
doaj   +1 more source

Hexapod Locomotion Across Structured and Unstructured Terrains: A Data‐Driven Review of Modeling, Control, and Validation

Journal of Field Robotics, EarlyView.
ABSTRACT The design of a hexapod is complex and requires integration between kinematic models, control systems, and sensing. Existing literature has reviewed these sub‐systems in isolation. Since 2021, there has been no review of the field despite significant advancements in soft soil, lunar traversal, and artificial intelligence.
Akhil Rampersad, Bashan Naidoo
wiley   +1 more source

Numerical benchmarking of dual decomposition-based optimization algorithms for distributed model predictive control

Results in Control and Optimization
This paper presents a benchmark study of dual decomposition-based distributed optimization algorithms applied to constraint-coupled model predictive control problems.
Vassilios Yfantis, Achim Wagner, Martin Ruskowski   +2 more
doaj   +1 more source

Asynchronous Parallel Stochastic Quasi-Newton Methods. [PDF]

Parallel Comput, 2021
Tong Q, Liang G, Cai X, Zhu C, Bi J.
europepmc   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

A Compact Annular Electrostatic Clutch Joint: Dynamic Response Modeling and Time‐Sharing Control for Underactuated Robots

SmartBot, EarlyView.
Electrostatic clutches offer programmable variable stiffness for multi‐DOF robots, but their continuous motion is usually bottlenecked by spatial constraints and detachment delays. Here, the authors report a compact annular electrostatic clutch joint with a biphasic amplitude‐frequency modulation strategy to rapidly mitigate residual polarization ...
Haochen Yong, Jian Wang, Zhisheng Xia, Zhexuan Li, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup. [PDF]

Med Phys, 2023
Liu Y, Zhang M, Zhong Z, Zeng X.
europepmc   +1 more source

Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi‐scenario applications, and translational prospects

Smart Molecules, EarlyView.
AI is transforming TPD by improving the design, prediction, and optimization of degraders such as PROTACs, molecular glues, and LYTACs. This review summarizes key AI‐driven advances, highlights applications across drug discovery stages, and discusses remaining challenges and future directions for accelerating the development of therapies against ...
Shuanglin Qin, Rui Peng, Guangshuai Zhang, Si Yan, Jin Xiao, Zishu Liu, Ziyu Tan, Qingqing Xie, Shangjie Li, Wei Luo, Xiaohe Xiao   +10 more
wiley   +1 more source

Computing the Projection on the Intersection of Linear Equality and Cardinality Constraints

IEEE Access
In this paper, we introduce a novel approach to solve the vector projection problem under linear equality and cardinality constraints, termed the Quasi-Newton Lagrangian method. This approach employs a Lagrangian transformation to address linear equality
Xiao-Jing Wang, Zhen-Sheng Yu
doaj   +1 more source

A Novel Approach to Energy Management in Electric Steelworks

steel research international, EarlyView.
Feed‐forward neural networks are exploited to estimate electric energy consumptions of the electric arc furnace and ladle furnace processes. The models are used to optimize production schedule so that more energy intensive grades are produced when the cost of energy is lower.
Valentina Colla, Stefano Dettori, Silvia Cateni, Marco Vannucci, Antonella Vignali, Claudio Mocci, Irene Dovichi, Davide Chionna, Lorenzo Vannini, Enrico Paluzzano, Costanzo Pietrosanti, Davide Onesti, Daniele Venier   +12 more
wiley   +1 more source