arXiv subjects

Heping Zhang

Publications and source records attributed to Heping Zhang.

At least 55 records · Page 3Linked to original sources

arXiv2022

Star Structure Connectivity of Folded hypercubes and Augmented cubes

The connectivity is an important parameter to evaluate the robustness of a network. As a generalization, structure connectivity and substructure connectivity of graphs were proposed. For connected graphs $G$ and $H$, the $H$-structure connectivity $κ(G; H)$ (resp. $H$-substructure connectivity $κ^{s}(G; H)$) of $G$ is the minimum cardinality of a set of subgraphs $F$ of $G$ that each is isomorphic to $H$ (resp. to a connected subgraph of $H$) so that $G-F$ is disconnected or the singleton. As popular variants of hypercubes, the $n$-dimensional folded hypercubes $FQ_{n}$ and augmented cubes $AQ_{n}$ are attractive interconnected network prototypes for multiple processor systems. In this paper, we obtain that $κ(FQ_{n};K_{1,m})=κ^{s}(FQ_{n};K_{1,m})=\lceil\frac{n+1}{2}\rceil$ for $2\leqslant m\leqslant n-1$, $n\geqslant 7$, and $κ(AQ_{n};K_{1,m})=κ^{s}(AQ_{n};K_{1,m})=\lceil\frac{n-1}{2}\rceil$ for $4\leqslant m\leqslant \frac{3n-15}{4}$.

math.CO↗

arXiv2021

Some tight bounds on the minimum and maximum forcing numbers of graphs

Let $G$ be a simple graph with $2n$ vertices and a perfect matching. We denote by $f(G)$ and $F(G)$ the minimum and maximum forcing number of $G$, respectively. Hetyei obtained that the maximum number of edges of graphs $G$ with a unique perfect matching is $n^2$. We know that $G$ has a unique perfect matching if and only if $f(G)=0$. Along this line, we generalize the classical result to all graphs $G$ with $f(G)=k$ for $0\leq k\leq n-1$, and characterize corresponding extremal graphs as well. Hence we get a non-trivial lower bound of $f(G)$ in terms of the order and size. For bipartite graphs, we gain corresponding stronger results. Further, we obtain a new upper bound of $F(G)$. For bipartite graphs $G$, Che and Chen (2013) obtained that $f(G)=n-1$ if and only if $G$ is complete bipartite graph $K_{n,n}$. We completely characterize all bipartite graphs $G$ with $f(G)= n-2$.

math.CO↗

arXiv2021

The complete forcing numbers of hexagonal systems

Let G be a graph with a perfect matching. A complete forcing set of G is a subset of edges of G to which the restriction of every perfect matching is a forcing set of it. The complete forcing number of G is the minimum cardinality of complete forcing sets of G. Xu et al. gave a characterization for a complete forcing set and derived some explicit formulas for the complete forcing numbers of cata-condensed hexagonal systems. In this paper, we consider general hexagonal systems. We present an upper bound on the complete forcing numbers of hexagonal systems in terms of elementary edge-cut cover and two lower bounds by the number of hexagons and matching number respectively. As applications, we obtain some explicit formulas for the complete forcing numbers of some types of hexagonal systems including parallelogram, regular hexagon- and rectangle-shaped hexagonal systems.

math.CO↗

arXiv2020

The star-structure connectivity and star-substructure connectivity of hypercubes and folded hypercubes

As a generalization of vertex connectivity, for connected graphs $G$ and $T$, the $T$-structure connectivity $κ(G, T)$ (resp. $T$-substructure connectivity $κ^{s}(G, T)$) of $G$ is the minimum cardinality of a set of subgraphs $F$ of $G$ that each is isomorphic to $T$ (resp. to a connected subgraph of $T$) so that $G-F$ is disconnected. For $n$-dimensional hypercube $Q_{n}$, Lin et al. [6] showed $κ(Q_{n},K_{1,1})=κ^{s}(Q_{n},K_{1,1})=n-1$ and $κ(Q_{n},K_{1,r})=κ^{s}(Q_{n},K_{1,r})=\lceil\frac{n}{2}\rceil$ for $2\leq r\leq 3$ and $n\geq 3$. Sabir et al. [11] obtained that $κ(Q_{n},K_{1,4})=κ^{s}(Q_{n},K_{1,4})=\lceil\frac{n}{2}\rceil$ for $n\geq 6$, and for $n$-dimensional folded hypercube $FQ_{n}$, $κ(FQ_{n},K_{1,1})=κ^{s}(FQ_{n},K_{1,1})=n$, $κ(FQ_{n},K_{1,r})=κ^{s}(FQ_{n},K_{1,r})=\lceil\frac{n+1}{2}\rceil$ with $2\leq r\leq 3$ and $n\geq 7$. They proposed an open problem of determining $K_{1,r}$-structure connectivity of $Q_n$ and $FQ_n$ for general $r$. In this paper, we obtain that for each integer $r\geq 2$, $κ(Q_{n};K_{1,r})=κ^{s}(Q_{n};K_{1,r})=\lceil\frac{n}{2}\rceil$ and $κ(FQ_{n};K_{1,r})=κ^{s}(FQ_{n};K_{1,r})= \lceil\frac{n+1}{2}\rceil$ for all integers $n$ larger than $r$ in quare scale. For $4\leq r\leq 6$, we separately confirm the above result holds for $Q_n$ in the remaining cases.

math.CO↗

arXiv2020

Some novel minimax results for perfect matchings of hexagonal systems

The anti-forcing number of a perfect matching $M$ of a graph $G$ is the minimum number of edges of $G$ whose deletion results in a subgraph with a unique perfect matching $M$, denoted by $af(G,M)$. When $G$ is a plane bipartite graph, Lei et al. established a minimax result: For any perfect matching $M$ of $G$, $af(G,M)$ equals the maximum number of $M$-alternating cycles of $G$ where any two either are disjoint or intersect only at edges in $M$; For a hexagonal system, the maximum anti-forcing number equals the fries number. In this paper we show that for every perfect matching $M$ of a hexagonal system $H$ with the maximum anti-forcing number or minus one, $af(H,M)$ equals the number of $M$-alternating hexagons of $H$. Further we show that a hexagonal system $H$ has a triphenylene as nice subgraph if and only $af(H,M)$ always equals the number of $M$-alternating hexagons of $H$ for every perfect matching $M$ of $H$.

math.CO↗

arXiv2020

Relations between global forcing number and maximum anti-forcing number of a graph

The global forcing number of a graph G is the minimal cardinality of an edge subset discriminating all perfect matchings of G, denoted by gf(G). For any perfect matching M of G, the minimal cardinality of an edge subset S in E(G)-M such that G-S has a unique perfect matching is called the anti-forcing number of M,denoted by af(G, M). The maximum anti-forcing number of G among all perfect matchings is denoted by Af(G). It is known that the maximum anti-forcing number of a hexagonal system equals the famous Fries number. We are interested in some comparisons between the global forcing number and the maximum anti-forcing number of a graph. For a bipartite graph G, we show that gf(G)is larger than or equal to Af(G). Next we mainly extend such result to non-bipartite graphs, which is the set of all graphs with a perfect matching which contain no two disjoint odd cycles such that their deletion results in a subgraph with a perfect matching. For any such graph G, we also have gf(G) is larger than or equal to Af(G) by revealing further property of non-bipartite graphs with a unique perfect matching. As a consequence, this relation also holds for the graphs whose perfect matching polytopes consist of non-negative 1-regular vectors. In particular, for a brick G, de Carvalho, Lucchesi and Murty [4] showed that G satisfying the above condition if and only if G is solid, and if and only if its perfect matching polytope consists of non-negative 1-regular vectors. Finally, we obtain tight upper and lower bounds on gf(G)-Af(G). For a connected bipartite graph G with 2n vertices, we have that 0 \leq gf(G)-Af(G) \leq 1/2 (n-1)(n-2); For non-bipartite case, -1/2 (n^2-n-2) \leq gf(G)-Af(G) \leq (n-1)(n-2).

math.CO↗

arXiv2020

A super scalable algorithm for short segment detection

In many applications such as copy number variant (CNV) detection, the goal is to identify short segments on which the observations have different means or medians from the background. Those segments are usually short and hidden in a long sequence, and hence are very challenging to find. We study a super scalable short segment (4S) detection algorithm in this paper. This nonparametric method clusters the locations where the observations exceed a threshold for segment detection. It is computationally efficient and does not rely on Gaussian noise assumption. Moreover, we develop a framework to assign significance levels for detected segments. We demonstrate the advantages of our proposed method by theoretical, simulation, and real data studies.

stat.ME↗

arXiv2019

Hierarchical Change-Point Detection for Multivariate Time Series via a Ball Detection Function

Sequences of random objects arise from many real applications, including high throughput omic data and functional imaging data. Those sequences are usually dependent, non-linear, or even Non-Euclidean, and an important problem is change-point detection in such dependent sequences in Banach spaces or metric spaces. The problem usually requires the accurate inference for not only whether changes might have occurred but also the locations of the changes when they did occur. To this end, we first introduce a Ball detection function and show that it reaches its maximum at the change-point if a sequence has only one change point. Furthermore, we propose a consistent estimator of Ball detection function based on which we develop a hierarchical algorithm to detect all possible change points. We prove that the estimated change-point locations are consistent. Our procedure can estimate the number of change-points and detect their locations without assuming any particular types of change-points as a change can occur in a sequence in different ways. Extensive simulation studies and analyses of two interesting real datasets wind direction and Bitcoin price demonstrate that our method has considerable advantages over existing competitors, especially when data are non-Euclidean or when there are distributional changes in the variance.

math.ST↗

arXiv2018

Characterizing the fullerene graphs with the minimum forcing number 3

The minimum forcing number of a graph $G$ is the smallest number of edges simultaneously contained in a unique perfect matching of $G$. Zhang, Ye and Shiu \cite{HDW} showed that the minimum forcing number of any fullerene graph was bounded below by $3$. However, we find that there exists exactly one excepted fullerene $F_{24}$ with the minimum forcing number $2$. In this paper, we characterize all fullerenes with the minimum forcing number $3$ by a construction approach. This also solves an open problem proposed by Zhang et al. We also find that except for $F_{24}$, all fullerenes with anti-forcing number $4$ have the minimum forcing number $3$. In particular, the nanotube fullerenes of type $(4, 2)$ are such fullerenes.

math.CO↗

arXiv2017

Tight upper bound on the maximum anti-forcing numbers of graphs

Let $G$ be a simple graph with a perfect matching. Deng and Zhang showed that the maximum anti-forcing number of $G$ is no more than the cyclomatic number. In this paper, we get a novel upper bound on the maximum anti-forcing number of $G$ and investigate the extremal graphs. If $G$ has a perfect matching $M$ whose anti-forcing number attains this upper bound, then we say $G$ is an extremal graph and $M$ is a nice perfect matching. We obtain an equivalent condition for the nice perfect matchings of $G$ and establish a one-to-one correspondence between the nice perfect matchings and the edge-involutions of $G$, which are the automorphisms $α$ of order two such that $v$ and $α(v)$ are adjacent for every vertex $v$. We demonstrate that all extremal graphs can be constructed from $K_2$ by implementing two expansion operations, and $G$ is extremal if and only if one factor in a Cartesian decomposition of $G$ is extremal. As examples, we have that all perfect matchings of the complete graph $K_{2n}$ and the complete bipartite graph $K_{n, n}$ are nice. Also we show that the hypercube $Q_n$, the folded hypercube $FQ_n$ ($n\geq4$) and the enhanced hypercube $Q_{n, k}$ ($0\leq k\leq n-4$) have exactly $n$, $n+1$ and $n+1$ nice perfect matchings respectively.

math.CO↗

arXiv2017

Fractional matching preclusion number of graphs

Let $G$ be a graph with an even number of vertices. The matching preclusion number of $G$, denoted by $mp(G)$, is the minimum number of edges whose deletion leaves the resulting graph without a perfect matching. We introduced a $0$-$1$ linear programming which can be used to find matching preclusion number of graphs. In this paper, by relaxing of the $0$-$1$ linear programming we obtain a linear programming and call its optimal objective value as fractional matching preclusion number of graph $G$, denoted by $mp_f(G)$. We show $mp_f(G)$ can be computed in polynomial time for any graph $G$. By using perfect matching polytope, we transform it as a new linear programming whose optimal value equals the reciprocal of $mp_f(G)$. For bipartite graph $G$, we obtain an explicit formula for $mp_f(G)$ and show that $\lfloor mp_f(G) \rfloor$ is the maximum integer $k$ such that $G$ has a $k$-factor. Moreover, for any two bipartite graphs $G$ and $H$, we show $mp_f(G \square H) \geqslant mp_f(G)+\lfloor mp_f(H) \rfloor$, where $G \square H$ is the Cartesian product of $G$ and $H$.

math.CO↗

arXiv2017

On the forcing spectrum of generalized Petersen graphs P(n,2)

The forcing number of a perfect matching $M$ of a graph $G$ is the smallest cardinality of subsets of $M$ that are contained in no other perfect matchings of $G$. The forcing spectrum of $G$ is the collection of forcing numbers of all perfect matchings of $G$. In this paper, we classify the perfect matchings of a generalized Petersen graph $P(n,2)$ in two types, and show that the forcing spectrum is the union of two integer intervals. For $n\ge 34$, it is $\left[\lceil \frac { n }{ 12 } \rceil+1,\lceil \frac { n+3 }{ 7 } \rceil +δ(n)\right]\cup \left[\lceil \frac { n+2 }{ 6 } \rceil,\lceil \frac { n }{ 4 } \rceil\right]$, where $δ(n)=1$ if $n\equiv 3$ (mod 7), and $δ(n)=0$ otherwise.

math.CO↗

arXiv2016

Permanental polynomials of skew adjacency matrices of oriented graphs

Let $G^σ$ be an orientation of a simple graph $G$. In this paper, the permanental polynomial of an oriented graph $G^σ$ is introduced. The coefficients of the permanental polynomial of $G^σ$ are interpreted in terms of the graph structure of $G^σ$, and it is proved that all orientations $G^σ$ of $G$ have the same permanental polynomial if and only if $G$ has no even cycles. Furthermore, the roots of the permanental polynomial of $G^σ$ are studied.

math.CO↗

arXiv2016

Matching preclusion for $n$-grid graphs

A matching preclusion set of a graph is an edge set whose deletion results in a graph without perfect matching or almost perfect matching. The Cartesian product of $n$ paths is called an $n$-grid graph. In this paper, we study the matching preclusion problems for $n$-grid graphs and obtain the following results. If an $n$-grid graph has an even order, then it has the matching preclusion number $n$, and every optimal matching preclusion set is trivial. If the $n$-grid graph has an odd order, then it has the matching preclusion number $n+1$, and all the optimal matching preclusion sets are characterized.

math.CO↗

arXiv2016

Extremal anti-forcing numbers of perfect matchings of graphs

The anti-forcing number of a perfect matching $M$ of a graph $G$ is the minimal number of edges not in $M$ whose removal to make $M$ as a unique perfect matching of the resulting graph. The set of anti-forcing numbers of all perfect matchings of $G$ is the anti-forcing spectrum of $G$. In this paper, we characterize the plane elementary bipartite graph whose minimum anti-forcing number is one. We show that the maximum anti-forcing number of a graph is at most its cyclomatic number. In particular, we characterize the graphs with the maximum anti-forcing number achieving the upper bound, such extremal graphs are a class of plane bipartite graphs. Finally, we determine the anti-forcing spectrum of an even polygonal chain in linear time.

math.CO↗

arXiv2016

Multiple Change-point Detection: a Selective Overview

Very long and noisy sequence data arise from biological sciences to social science including high throughput data in genomics and stock prices in econometrics. Often such data are collected in order to identify and understand shifts in trend, e.g., from a bull market to a bear market in finance or from a normal number of chromosome copies to an excessive number of chromosome copies in genetics. Thus, identifying multiple change points in a long, possibly very long, sequence is an important problem. In this article, we review both classical and new multiple change-point detection strategies. Considering the long history and the extensive literature on the change-point detection, we provide an in-depth discussion on a normal mean change-point model from aspects of regression analysis, hypothesis testing, consistency and inference. In particular, we present a strategy to gather and aggregate local information for change-point detection that has become the cornerstone of several emerging methods because of its attractiveness in both computational and theoretical properties.

stat.ME↗

arXiv2016

Computing Affine Combinations, Distances, and Correlations for Recursive Partition Functions

Recursive partitioning is the core of several statistical methods including CART, random forest, and boosted trees. Despite the popularity of tree based methods, to date, there did not exist methods for combining multiple trees into a single tree, or methods for systematically quantifying the discrepancy between two trees. Taking advantage of the recursive structure in trees we formulated fast algorithms for computing affine combinations, distances and correlations in a vector subspace of recursive partition functions.

cs.DS↗

arXiv2016

Construction and characterization of graphs whose each spanning tree has a perfect matching

An edge subset $S$ of a connected graph $G$ is called an anti-Kekulé set if $G-S$ is connected and has no perfect matching. We can see that a connected graph $G$ has no anti-Kekulé set if and only if each spanning tree of $G$ has a perfect matching. In this paper, by applying Tutte's 1-factor theorem and structure of minimally 2-connected graphs, we characterize all graphs whose each spanning tree has a perfect matching In addition, we show that if $G$ is a connected graph of order $2n$ for a positive integer $n\geq 4$ and size $m$ whose each spanning tree has a perfect matching, then $m\leq \frac{(n+1)n} 2$, with equality if and only if $G\cong K_n\circ K_1$.

math.CO↗