Results 51 to 60 of about 373 (214)

Tensor‐Based Reduction of Linear Parameter‐Varying State‐Space Models

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT The linear parameter‐varying (LPV) framework is a powerful tool for controlling nonlinear (NL) and complex systems, but the conversion of NL models into LPV forms often results in high‐dimensional and overly conservative LPV models. To be able to apply control strategies, there is often a need for model reduction in order to reduce ...
Bogoljub Terzin, E. Javier Olucha, Amritam Das, Siep Weiland, Roland Tóth   +4 more
wiley   +1 more source

The role of identification in data‐driven policy iteration: A system theoretic study

International Journal of Robust and Nonlinear Control, EarlyView.
Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
wiley   +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

Reverse engineering strut‐and‐tie models for assessing reinforced concrete structures

Structural Concrete, EarlyView.
Abstract Strut‐and‐tie models enable the design of reinforced concrete structures with static or geometrical discontinuities, providing interpretability and control over the load path. These models are valuable for designing discontinuity regions of new structures and for validating nonlinear finite‐element analysis results. However, developing a strut‐
Karin Yu, Walter Kaufmann
wiley   +1 more source

Multiple-term improvements of Jensen's inequality for (p,h)-convex and (p,h)-log convex functions

Journal of Mathematical Inequalities
Summary: In this paper, we present several new multiple-term improvements of Jensen's inequality for \((p, h)\)-convex and \((p, h)\)-log convex functions. As applications of our results, we present new bounds by employing means and Hölder type inequalities for the symmetric norms for \(\tau\)-measurable operators. We make links between ourfindings and
Huy, Duong Quoc, Gourty, Abdelmajid, Ighachane, Mohamed Amine, Boumazgour, Mohamed   +3 more
openaire   +2 more sources

Movement and Space Use Patterns of the Beale's Eyed Turtle (Sacalia bealei) Suggest Sensitivity to Environmental Changes and Poaching 比氏眼斑龟 (Sacalia bealei) 的活动与空间利用模式揭示其对环境变化及盗猎的敏感性

Wildlife Letters, EarlyView.
Using radiotelemetry, we found that the movement and home range of the endangered Sacalia bealei varied significantly across reproductive classes and seasons, with males exhibiting greater movement than females during wet and mating seasons. The species exhibits strong aquatic dependence, favoring deep pools interspaced among riffle‐pool sequences ...
Wing Sing Chan, Jonathan J. Fong, Timothy C. Bonebrake, Yik‐Hei Sung   +3 more
wiley   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +5 more
wiley   +1 more source

Double‐Integration‐Enhanced Stochastic Gradient Descent Based on Neural Dynamics for Improving Generalisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Generalisation is a crucial aspect of deep learning, enabling models to perform well on unseen data. Currently, most optimisers that improve generalisation typically suffer from efficiency bottlenecks. This paper proposes a double‐integration‐enhanced stochastic gradient descent (DIESGD) optimiser, which treats the negative gradient as an ...
Ting Li, Longbang Wang, Jiexing Li, Jicheng Li   +3 more
wiley   +1 more source

LLM‐Powered Data Synthesis on Blockchain for Fusion Isomerism Learning in Heterogeneous Federated Systems

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Severe data starvation, architectural heterogeneity and Byzantine vulnerabilities fundamentally impede the deployment of robust multiclass classification models in decentralised edge environments. To address these intertwined challenges, we propose fusion isomerism learning (FusionIL), a secure and domain‐agnostic framework that ...
Zhihao Hao, Longbing Cao, Han Yu, Xiaoqiang Teng, Guancheng Wang, Chuanbin Zhang   +5 more
wiley   +1 more source

Hermite-Hadamard type inequalities for multiplicatively m-convex functions

Boletim da Sociedade Paranaense de Matemática
Convex functions play an important role in finding the inequalities, those help in finding the solutions of different types of equations and equations involving functions. In this article we have considered investigated on the m-convex functions in a normed linear space. We have established some results of Hermite-Hadamard like inequality.
Ashok Kumar Sahoo, Bibhakar Kodamasingh, Binod Chandra Tripathy   +2 more
openaire   +1 more source