Results 121 to 130 of about 1,624,240 (288)

Spectral properties of edge Laplacian matrix

, 2023
Let $N(X)$ be the Laplacian matrix of a directed graph obtained from the edge adjacency matrix of a graph $X.$ In this work, we study the bipartiteness property of the graph with the help of $N(X).$ We computed the spectrum of the edge Laplacian matrix ...
Chauhan, Shivani, Reddy, A. Satyanarayana   +1 more
core  

Frequency Shaping for Improving a Trade‐Off Between Control and Privacy Performance: Beyond Differential Privacy

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In privacy protection of control systems, a trade‐off between control performance and privacy level is often pointed out. Our goal in this paper is to improve this trade‐off by shaping the frequency of noise added for privacy protection when the control objective is to track a reference signal, which is taken as a piece of information whose ...
Rintaro Watanabe, Yu Kawano, Nobutaka Wada, Ming Cao   +3 more
wiley   +1 more source

Initial State Privacy of Nonlinear Systems on Riemannian Manifolds

International 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

On spectrum and energies of enhanced power graphs

Mathematics Open
The enhanced power graph [Formula: see text] of a group G is a simple graph with vertex set G and two distinct vertex are adjacent if and only if they belong to the same cyclic subgroup.
Pankaj Kalita, Prohelika Das
doaj   +1 more source

PARSEC.py: A Python-Based Real-Space Kohn-Sham Density Functional Theory Code Accelerated by Machine Learned Charge Density. [PDF]

J Comput Chem
PARSEC.py is a Python‐based real‐space Kohn–Sham DFT framework that leverages the Python scientific ecosystem for transparent, modular integration of machine‐learned densities and GPU acceleration. This unified design enables more efficient and scalable first‐principles simulations of large chemical and materials systems. ABSTRACT PARSEC.py is a Python‐
Zhang Z, Perez CM, Kwon P, Head-Gordon M, Qian J.   +4 more
europepmc   +2 more sources

The study of the Laplacian Eignvalues of graphs

, 2011
碩士令G為一簡單圖且A(G)為圖G的鄰接矩陣，D(G)為圖G的度對角矩陣，其中對角線元素dii為圖G上的點vi的度數，即dii=deg(vi)。定義L(G)=D(G)–A(G)為圖G的拉普拉斯矩陣，此拉普拉斯矩陣的特徵值稱為圖G的拉普拉斯特徵值。已知任一圖的最小拉普拉斯特徵值必為零且其餘皆為正數，而其最大特徵值又稱為此圖的拉普拉斯譜半徑。 設f(n)為拉普拉斯譜半徑恰等於點數n且所有特徵值皆為整數的連通圖之總個數，Fiedler證明了圖G的拉普拉斯特徵值為其點數若且唯若圖G的補圖是不連通的 ...
戴思平; Tai, Su-Ping
core  

Fusion or Confusion? Assessing the Impact of Visible‐Thermal Image Fusion for Automated Wildlife Detection

Remote Sensing in Ecology and Conservation, EarlyView.
This study evaluates the performances of synchronous aerial visible (VIS) and thermal infrared (TIR) imagery for detecting great blue heron (Ardea herodias) nests and individuals using a YOLO11n model. VIS and TIR images were automatically aligned using deep learning, and both early and late fusion approaches were tested.
Camille Dionne‐Pierre, Samuel Foucher, Jérôme Théau, Jérôme Lemaître, Patrick Charbonneau, Maxime Brousseau, Mathieu Varin   +6 more
wiley   +1 more source

Cramer-Rao Bounds for Laplacian Matrix Estimation

CoRR
In this paper, we analyze the performance of the estimation of Laplacian matrices under general observation models. Laplacian matrix estimation involves structural constraints, including symmetry and null-space properties, along with matrix sparsity.
Morad Halihal, Tirza Routtenberg, H. Vincent Poor   +2 more
openaire   +2 more sources

Brain‐Inspired Neuromorphic Device for Artificial Intelligent Robots Applications

SmartBot, EarlyView.
Brain‐inspired neuromorphic devices mimic biological systems to provide an efficient hardware foundation for embodied intelligent robotics. This review explores the material systems and corresponding computing architectures of neuromorphic devices that support low‐power perception, adaptive learning, and real‐time decision‐making.
Jiachen Han, Zheng Wang, Tianyu Wang, Jialin Meng   +3 more
wiley   +1 more source

Graph Laplacian Connectivity Matrix

Ovaj rad istražuje koncept vršne povezanosti u teoriji grafova kroz analizu broja vršno disjunktnih putova između parova vrhova. U tom se kontekstu uvodi Laplaceova matrica povezanosti, definirana pomoću matrice vršne povezanosti,analogno načinu na koji ...
Vuković, Ante
core   +1 more source