In graph theory, a cycle graph or circular graph is a graph that consists of a single cycle, or in other words, some number of vertices (at least 3, if the graph is simple) connected in a closed chain. The cycle graph with n vertices is called C n. [2]

2025年3月5日 · In graph theory, a cycle graph C_n, sometimes simply known as an n-cycle (Pemmaraju and Skiena 2003, p. 248), is a graph on n nodes containing a single cycle through all nodes. A different sort of cycle graph, here termed a group cycle graph, is a graph which shows cycles of a group as well as the connectivity between the group cycles.

2022年9月2日 · The cycle graph with n vertices is called Cn. Properties of Cycle Graph:- It is a Connected Graph. A Cycle Graph or Circular Graph is a graph that consists of a single cycle. In a Cycle Graph number of vertices is equal to number of edges. A Cycle Graph is 2-edge colorable or 2-vertex colorable, if and only if it has an even number of vertices.

In mathematics, Cn refers to a cycle of size n. This concept is often used in graph theory and combinatorics to describe a particular type of graph. A cycle is a closed loop in a graph, where each vertex is connected to exactly two other vertices in the cycle.

In this report, we study graph complements Gn of cyclic graphs Cn or graph complements G+. of path graphs. Gn are circulant, vertex-transitive, claw-free, strongly regular, Hamiltonian graphs with. Zn symmetry and Shannon capacity 2. Also the Wiener and Harary index are known.

图神经网络（Graph Neural Networks, GNN）是一类用于处理图结构数据的神经网络模型，与传统的神经网络（例如卷积神经网络、循环神经网络等）处理规则数据结构（如图像、时间序列）不同，图神经网络专门处理不规则的图结构数据，如社交网络、知识图谱等。

可将 图 /网络 (Graph / Network)视为一个系统，以 G (N,E) 表示，由两种元素组成： 顶点 /节点 (Vertex/Node)，以 N 表示，和 边 /链接 (Edge/Link)，以 E 表示。 顶点和边具有属性 (Attribute)，边可能有方向 (有向图 Directed Graph)。 社交网络中，人是顶点，人和人之间的关系是边，人/顶点的属性比如年龄、性别、职业、爱好等构成了一个向量，类似的，边也可用向量来表示。 微信好友是双向的，你我互为好友 (不考虑拉黑/屏蔽)，对应于 无向图 (Undirected …

文章中，作者提出了两种方式构建图卷积神经网络：空域构建（Spatial Construction）和频域构建（Spectral Construction）。 空域构建主要考虑 (2) (3)两点，即CNN多尺度，层次，局部感受野的特点。 首先，我们先定义一个有权重的无向图 G= (\Omega, W) ，这里 \Omega 表示结点，大小为 m ， W 表示边，大小为 m\times m ，是一个对称的非负矩阵。 因此结点 j 的相邻结点可以表示为： N_\delta=\ {i\in\Omega: W_ {ij}>\delta\} \\ 空域卷积（Spatial Convolution） 图1 空域卷积示 …

I am trying to find out the spectrum (the collection of eigenvalues) with their multiplicities of the cycle graph $C_n$. Assuming that $X=\pmatrix{x_1\\x_2\\\vdots\\x_n}$ is the eigenvector, by considering $AX=\lambda X$, where $A$ is the adjacency matrix, I get …

Graph Convolution作为Graph Networks的一个分支，可以说几乎所有的图结构网络都是大同小异，详见综述[1]，而Graph Convolution Network又是Graph Networks中最简单的一个分支。理解了它便可以理解很多近年来的图…