Results 151 to 160 of about 341,235 (326)

Initial State Privacy of Nonlinear Systems on Riemannian Manifolds

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley   +1 more source

Algorithms in real algebraic geometry

open access: yes, 2011
Bu çalışmada Gröbner tabanlarının ve Homogeneous tabanlarının özellikleriverilmiştir. Bu bağlamda, polinom denklem sistemlerini çözmek için farklı yöntemlerverdik ve hangi tekniğin daha etkili olduğuna karar vermeye çalıştık.Anahtar Kelimeler: Polinom idealleri, Çok değişkenli polinomlar, Gröbner tabanları,Homogeneous tabanları, Polinon denklem ...
openaire   +2 more sources

A Cascaded Strategy With Embodied Artificial Intelligence: Forward Kinematics Solutions for CCRobot‐S

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT This paper presents a novel cable‐climbing mechanism: the Collaborative Climbing Robot Squad (CCRobot‐S), a variant of Reconfigurable Cable‐Driven Parallel Robots (R‐CDPR), specifically designed for the inspection and maintenance of stay cables.
Zhenliang Zheng   +4 more
wiley   +1 more source

On an Aggregation Theory for Indicators Expressing Behaviors of Complex Systems With an Application to Sustainability

open access: yesSustainable Development, EarlyView.
ABSTRACT Certain attributes of large‐scale complex systems are often expressed through sets of indicators. For example, the sustainability of an entity, be it a nation, a city, an energy system, a corporation etc., can be effectively represented by indicators and corresponding data series.
Vassilis S. Kouikoglou   +1 more
wiley   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

open access: yesCAAI 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   +5 more
wiley   +1 more source

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