3 research outputs found
Hyperbolic Circle Packings and Total Geodesic Curvatures on Surfaces with Boundary
This paper investigates a generalized hyperbolic circle packing (including
circles, horocycles or hypercycles) with respect to the total geodesic
curvatures on the surface with boundary. We mainly focus on the existence and
rigidity of circle packing whose contact graph is the -skeleton of a finite
polygonal cellular decomposition, which is analogous to the construction of
Bobenko and Springborn [4]. Motivated by Colin de Verdi\`ere's method [6], we
introduce the variational principle for generalized hyperbolic circle packings
on polygons. By analyzing limit behaviours of generalized circle packings on
polygons, we give an existence and rigidity for the generalized hyperbolic
circle packing with conical singularities regarding the total geodesic
curvature on each vertex of the contact graph. As a consequence, we introduce
the combinatoral Ricci flow to find a desired circle packing with a prescribed
total geodesic curvature on each vertex of the contact graph.Comment: 26 pages, 7 figure
Graph Optimization Model Fusing BLE Ranging with Wi-Fi Fingerprint for Indoor Positioning
To improve the user’s positioning accuracy of a Wi-Fi fingerprint-based positioning algorithm, this study proposes a graph optimization model based on the framework of g2o that fuses a Wi-Fi fingerprint and Bluetooth Low Energy (BLE) ranging technologies. In our model, the improvement in positioning can be formulated as a nonlinear least-squares optimization problem that a graph can represent. The graph regards users as nodes and our self-designed error functions between users as edges. In the graph, the nodes obtain the initial coordinates through Wi-Fi fingerprint positioning, and all error functions aggregate to a total error function to be solved. To improve the solution effect of the total error function and weaken the influence of measurement error, an information matrix, an edge selection principle, and a Huber kernel function are introduced. The Levenberg–Marquardt (LM) algorithm is used to solve the total error function and the affine transformation estimation is used for the drifting solution. Through experiments, the influence of the threshold in the Huber kernel function is explored, the relationship between the number of nodes in the graph and the optimization effect is analyzed, and the impact of the distribution of nodes is researched. The experimental results show improvements in the positioning accuracy of four common Wi-Fi fingerprint-matching algorithms: KNN, WKNN, GK, and Stg