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Indonesian Journal of Combinatorics
Let $B(G)$ be the incidence matrix of a graph $G$. The row in $B(G)$ corresponding to a vertex $v$, denoted by $s(v)$ is the string which belongs to $\Bbb{Z}_2^n$, a set of $n$-tuples over a field of order two. The Hamming distance between the strings $s(u)$ and $s(v)$ is the number of positions in which $s(u)$ and $s(v)$ differ. In this paper we obtain the Hamming distance between the strings generated by the incidence matrix of a graph. The sum of Hamming distances between all pairs of strings, called Hamming index of a graph is obtained.
2018
Hamming distance of a two bit strings u and v of length n is defined to be the number of positions of u and v with different digit. If G is a simple graph on n vertices and m edges and B is an edge–vertex incidence matrix of G, then every edge e of G can be labeled using a binary digit string of length n from the row of B which corresponds to the edge e. We discuss Hamming distance of two different edges of the graph G. Then, we present formulae for the sum of all Hamming distances between two different edges of G, particularly when G is a path, a cycle, and a wheel, and some composite graphs.
Let G be a graph on n vertices and B0(G) be its edge-vertex incidence matrix. The row in B0(G) corresponding to an edge e, denoted by s(e) is a string which belongs to Zn2 , a set of n-tuples over a field of order two. The Hamming distance between the strings s(e) and s(f) is the number of positions in which s(e) and s(f) differ. Hamming index of a graph is the sum of Hamming distances between all pairs of strings. In this paper we obtain the Hamming index of graphs generated by an edge-vertex incidence matrix along with an algorithm.
Journal of Physics: Conference Series
For example G(V,E) becomes graph on p nodes and q sides and B'(G) called being side-node incidence matrix from G. Every side e of G can be labeled using a binary digit string of length n from the row of B'(G) which corresponds to the side e, denoted by s(e). The Hamming distance between the strings s(e) and s(f) of length n is defined to be the number of positions of s(e) and s(f) with different digit. Hamming index from a graph is the number of Hamming distances between all pairs of strings. In this research, author discuss the Hamming index of graphs produced by an side-node incidence matrix, particularly windmill graph and snake graphs.
ArXiv, 2020
In this paper, we examine the binary linear codes with respect to Hamming metric from incidence matrix of a unit graph $G(\mathbb{Z}_{n})$ with vertex set is $\mathbb{Z}_{n}$ and two distinct vertices $x$ and $y$ being adjacent if and only if $x+y$ is unit. The main parameters of the codes are given.
In this paper, we introduce a new distance-based topological index of a graph G, called a k-distance degree index. It is defined as N k (G) = diam(G) ∑ k=1 (∑ v∈V (G) d k (v))k, where d k (v) = |N k (v)| = |{u ∈ V (G) : d(v, u) = k}| is the k-distance degree of a vertex v in G, d(u, v) is the distance between vertices u and v in G and diam(G) is the diameter of G. Exact formulas of the N k-index for some well-known graphs are presented. Bounds for N k-index and some other interesting results are established. It is shown that, N k-index of any graph G is an even integer number. In addition, an explicit formulae of a cartesian product of graphs are presented and we apply this result to compute the N k-index of some graphs (of chemical and computer science interest) like hypercube Q d , Hamming graphs H(d, n), nanotube R = P n 2C m and nanotori S = C n 2C m , etc.
Applied Mathematics Letters, 2011
The competition graph of a digraph D is a graph which has the same vertex set as D and has an edge between x and y if and only if there exists a vertex v in D such that (x, v) and (y, v) are arcs of D. For any graph G, G together with sufficiently many isolated vertices is the competition graph of some acyclic digraph. The competition number k(G) of a graph G is defined to be the smallest number of such isolated vertices. In general, it is hard to compute the competition number k(G) for a graph G and it has been one of important research problems in the study of competition graphs to characterize a graph by its competition number. In this paper, we give the exact values of the competition numbers of ternary Hamming graphs.
Proceedings of the American Mathematical Society, Series B
Let D D denote the distance matrix for an n + 1 n+1 point metric space ( X , d ) (X,d) . In the case that X X is an unweighted metric tree, the sum of the entries in D − 1 D^{-1} is always equal to 2 / n 2/n . Such trees can be considered as affinely independent subsets of the Hamming cube H n H_n , and it was conjectured that the value 2 / n 2/n was minimal among all such subsets. In this paper we confirm this conjecture and give a geometric interpretation of our result which applies to any subset of H n H_n .
2016
In his pioneering paper on matroids in 1935, Whitney obtained a characterization for binary matroids and left a comment at end of the paper that the problem of characterizing graphic matroids is the same as that of characterizing matroids which correspond to matrices (mod 2) with exactly two ones in each column. Later on Tutte obtained a characterization of graphic matroids in terms of forbidden minors in 1959. It is clear that Whitney indicated about incidence matrices of simple undirected graphs. Here we introduce the concept of a segment binary matroid which corresponds to matrices over Z_2 which has the consecutive 1's property (i.e., 1's are consecutive) for columns and obtained a characterization of graphic matroids in terms of this. In fact, we introduce a new representation of simple undirected graphs in terms of some vectors of finite dimensional vector spaces over Z_2 which satisfy consecutive 1's property. The set of such vectors is called a coding sequence of...
This study looked at Graph theory as it is an important part of mathematics. Topological indices are numerical parameters of a graph which describe its structure, they have many applications as tools for modeling chemical and other properties of molecules. In this paper, we presented some exact formulas of the Hyper-Zagreb index for some special graphs and some graph binary operations such disjunction G ∨ H, symmetric difference G ⊕ H, and tensor product G ⊗ H of graphs.
2012
Abstract We examine the p-ary codes, for any prime p, from the row span over F _p of| V|×| E| incidence matrices of connected graphs Γ=(V, E), showing that certain properties of the codes can be directly derived from the parameters and properties of the graphs.
Discrete Applied Mathematics, 2009
Linear Algebra and Its Applications, 2007
We show that the Hamming graph H(3,q)H(3,q) with diameter three is uniquely determined by its spectrum for q⩾36q⩾36. Moreover, we show that for given integer D⩾2D⩾2, any graph cospectral with the Hamming graph H(D,q)H(D,q) is locally the disjoint union of D copies of the complete graph of size q-1q-1, for q large enough.
2020
In this paper, we examine the linear codes with respect to the Hamming metric from incidence matrices of the zero-divisor graphs with vertex set is the set of all non-zero zero-divisors of the ring $\mathbb{Z}_n$ and two distinct vertices being adjacent iff their product is zero over $\mathbb{Z}_n.$ The main parameters of the codes are obtained.
A coloring of the vertices of a graph G is a distance k coloring of G if and only if any two vertices lying on a path of length less than or equal to k are given dierent colors. Hamming graphs are Cartesian (or box) products of complete graphs. In this paper, we will consider the interaction between coding theory and distance k colorings of Hamming graphs.
Information Processing Letters, 1997
Hamming graphs are, by definition, the Cartesian product of complete graphs. In the bipartite case these graphs are hypercubes. We present an algorithm recognizing Hamming graphs in linear time and space. This improves a previous algorithm which was linear in time but not in space. This also favorably compares to the general decomposition algorithms of graphs with respect to the Cartesian product, none of which is linear.
arXiv (Cornell University), 2024
The Q-polynomial property is an algebraic property of distance-regular graphs, that was introduced by Delsarte in his study of coding theory. Many distance-regular graphs admit the Q-polynomial property. Only recently the Q-polynomial property has been generalized to graphs that are not necessarily distance-regular. In [21] it was shown that graphs arising from the Hasse diagrams of the so-called attenuated space posets are Q-polynomial. These posets could be viewed as q-analogs of the Hamming posets, which were not studied in [21]. The main goal of this paper is to fill this gap by showing that the graphs arising from the Hasse diagrams of the Hamming posets are Q-polynomial.
Advances in Mathematics of Communications, 2011
... Hamming graphs $H^k(n,2)$ for $k \geq 2$. doi:10.3934/amc.2011.5.373 Full text: (518.6K) Jennifer D. Key - Department of Mathematics and Applied Mathematics, University of the Western Cape, 7535 Bellville, South Africa (email). ...
Classical, Semi-classical and Quantum Noise, 2011
This paper is a tutorial on the application of graph theoretic techniques in classical coding theory. A fundamental problem in coding theory is to determine the maximum size of a code satisfying a given minimum Hamming distance. This problem is thought to be extremely hard and still not completely solved. In addition to a number of closed form expressions for special cases and some numerical results, several relevant bounds have been derived over the years.
We show that any isometric irredundant embedding of a graph into a product of complete graphs is the canonical isometric embedding. This result is used to design a simple O(mn) algorithm for recognizing Hamming graphs.
European Journal of Combinatorics, 1996
This paper contains a new algorithm that recognizes whether a given graph G is a Hamming graph , i . e . a Cartesian product of complete graphs , in O ( m ) time and O ( n 2 ) space . Here m and n denote the numbers of edges and vertices of G , respectively . Previously this was only possible in O ( m log n ) time .
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