<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">ALAMT</journal-id><journal-title-group><journal-title>Advances in Linear Algebra &amp; Matrix Theory</journal-title></journal-title-group><issn pub-type="epub">2165-333X</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/alamt.2018.81006</article-id><article-id pub-id-type="publisher-id">ALAMT-83136</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Physics&amp;Mathematics</subject></subj-group></article-categories><title-group><article-title>
 
 
  A Note on the Spectral Radius of Weighted Signless Laplacian Matrix
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Şerife</surname><given-names>Büyükköse</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Nurşah</surname><given-names>Mutlu</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Gülistan</surname><given-names>Kaya Gök</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Departments of Mathematics, Faculty of Sciences, Gazi University, Ankara, Turkey</addr-line></aff><aff id="aff2"><addr-line>Department of Mathematics Education, Hakkari University, Hakkari, Turkey</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>sbuyukkose@gazi.edu.tr(ŞB)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>09</day><month>01</month><year>2018</year></pub-date><volume>08</volume><issue>01</issue><fpage>53</fpage><lpage>63</lpage><history><date date-type="received"><day>6,</day>	<month>November</month>	<year>2017</year></date><date date-type="rev-recd"><day>17,</day>	<month>March</month>	<year>2018</year>	</date><date date-type="accepted"><day>20,</day>	<month>March</month>	<year>2018</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  A weighted graph is a graph that has a numeric label associated with each edge, called the weight of edge. In many applications, the edge weights are usually represented by nonnegative integers or square matrices. The weighted signless Laplacian matrix of a weighted graph is defined as the sum of adjacency matrix and degree matrix of same weighted graph. In this paper, a brief overview of the notation and concepts of weighted graphs that will be used throughout this study is given. In Section 2, the weighted signless Laplacian matrix of simple connected weighted graphs is considered, some upper bounds for the spectral radius of the weighted signless Laplacian matrix are obtained and some results on weighted and unweighted graphs are found.
 
</p></abstract><kwd-group><kwd>Weighted Graph</kwd><kwd> Weighted Signless Laplacian Matrix</kwd><kwd> Spectral Radius</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>A weighted graph is a graph that has a numeric label associated with each edge, called the weight of edge. In many applications, the edge weights are usually represented by nonnegative integers or square matrices. In this paper, we generally deal with simple connected weighted graphs where the edge weights are positive definite square matrices. Let G = ( V , E ) be a simple connected weighted graph with vertex set V = { 1 , 2 , ⋯ , n } . Let w i j be the positive definite weight matrix of order t of the edge ij and assume that w i j = w j i . The weight of a vertex i ∈ V defined as w i = ∑ j : j ~ i w i j ; where i ~ j denotes the vertex j is adjacent to i.</p><p>Unless otherwise specified, by a weighted graph we mean a graph with each edge weight is a positive definite square matrix.</p><p>The weighted signless Laplacian matrix Q ( G ) of weighted graph G is a block matrix and defined as Q ( G ) = ( q i j ) n t &#215; n t , where</p><p>q i j = { w i ;         if   i = j , w i j ;       if   i ~ j , 0 ;         otherwise .</p><p>Clearly, Q ( G ) is a square matrix of order nt. The eigenvalues may be denoted by q 1 ( G ) , q 2 ( G ) , ⋯ , q n t ( G ) , where q 1 ( G ) ≥ q 2 ( G ) ≥ ⋯ ≥ q n t ( G ) . Also let q 1 ( G ) , q 1 ( w i ) and q 1 ( w i j ) denote the spectral radius of G and the largest eigenvalues of w i and w i j , respectively. If A ( G ) is the weighted adjacency matrix of G, then note that</p><p>Q ( G ) = W ( G ) + A ( G ) ,</p><p>where W ( G ) = d i a g ( w 1 , w 2 , ⋯ , w n ) .</p><p>In literature, there are a lot of studies deal with upper and lower bounds for the spectral radius of signless Laplacian matrix of unweighted graphs. For a simple connected and unweighted graph G, there are some known upper bounds on the spectral radius of signless Laplacian matrix as follows such that d i is</p><p>degree of vertex i and m i = 1 d i ∑ j : j ~ i d j .</p><p>q 1 ( G ) ≤ max i ∈ V { 2 d i } , (1)</p><p>q 1 ( G ) ≤ max i ∈ V { d i + m i } , (2)</p><p>q 1 ( G ) ≤ max i ∈ V { d i + d i + 8 d i m i 2 } , (3)</p><p>q 1 ( G ) ≤ max i ~ j { d i + d j } , (4)</p><p>q 1 ( G ) ≤ max i ~ j { d i + d j + ( d i − d j ) 2 + 4 m i m j 2 } . (5)</p><p>In this paper, some upper bounds for the spectral radius of signless Laplacian matrix of weighted graphs are given. Also some results on weighted and unweighted graphs are obtained by using these bounds. The following lemmas are convenient for the graphs we consider.</p><p>Lemma 1. [<xref ref-type="bibr" rid="scirp.83136-ref1">1</xref>] .</p><p>If A is a real symmetric n &#215; n matrix with eigenvalues q 1 ≥ q 2 ≥ ⋯ ≥ q n , then for any x &#175; ∈ ℝ n ( x &#175; ≠ 0 &#175; ) ,</p><p>q n x &#175; T x &#175; ≤ x &#175; T A x &#175; ≤ q 1 x &#175; T x &#175; .</p><p>The equality holds if and only if x &#175; is an eigenvector of A corresponding to the least eigenvalue q n .</p><p>Lemma 2. [<xref ref-type="bibr" rid="scirp.83136-ref2">2</xref>] .</p><p>If A is a real symmetric n &#215; n matrix with eigenvalues q 1 ≥ q 2 ≥ ⋯ ≥ q n then for any x &#175; ∈ ℝ n ( x &#175; ≠ 0 &#175; ) , y &#175; ∈ ℝ n ( y &#175; ≠ 0 &#175; ) ,</p><p>| x &#175; T A y &#175; | ≤ q 1 x &#175; T x &#175; y &#175; T y &#175; .</p><p>The equality holds if and only if x &#175; is an eigenvector of A corresponding to the largest eigenvalue q 1 and y &#175; = α x &#175; for some α ∈ ℝ .</p><p>Lemma 3. [<xref ref-type="bibr" rid="scirp.83136-ref3">3</xref>] .</p><p>Let G be a weighted graph and let w i j be the positive definite weight matrix of order t of the edge ij. Also let x &#175; be an eigenvector of w i j corresponding to the largest eigenvalue q 1 ( w i j ) for all i, j. Then</p><p>q 1 ( w i ) = ∑ j : j ~ i q 1 ( w i j ) .</p><p>Lemma 4. [<xref ref-type="bibr" rid="scirp.83136-ref4">4</xref>] .</p><p>Let G be a weighted graph and let w i j be the positive definite weight matrix of order t of the edge ij. If w i w i j + w i j w j and w i j w j k are not Hermitian matrices for all j, j∼i and for all k, k∼j, j∼i, then for any x &#175; ∈ ℂ n ( x &#175; ≠ 0 &#175; ) , y &#175; ∈ ℂ n ( y &#175; ≠ 0 &#175; ) ,</p><p>∑ j : j ~ i | x &#175; T ( w i w i j + w i j w j ) y &#175; | ≤ q 1 ( w i w i j + w i j w j ) x &#175; T x &#175; y &#175; T y &#175; , ∑ 1 ≤ i ,   k ≤ n ∑ k : k ~ i       k ~ j | x &#175; T w i j w j k y &#175; | ≤ q 1 ( w i j w j k ) x &#175; T x &#175; y &#175; T y &#175; .</p></sec><sec id="s2"><title>2. Main Results</title><p>In this section, some upper bounds for the spectral radius of weighted signless Laplacian matrix are found.</p><p>Theorem 5.</p><p>Let G be a simple connected weighted graph. Then</p><p>q 1 ( G ) ≤ max i ∈ V { 2 q 1 ( w i ) } . (6)</p><p>Proof.</p><p>Let x &#175; = ( x 1 &#175; T ,   x 2 &#175; T , ⋯ ,   x n &#175; T ) T be an eigenvector corresponding to the eigenvalue</p><p>q 1 ( G ) and x i &#175; be the vector component of x &#175; such that</p><p>x i &#175; T x i &#175; = max j ∈ V { x j &#175; T x j &#175; } . (7)</p><p>Since x &#175; is nonzero, so is x i &#175; . We have</p><p>q 1 ( G ) x &#175; = Q ( G ) x &#175; = W ( G ) x &#175; + A ( G ) x &#175; . (8)</p><p>From the i-th Equation of (8), we get</p><p>q 1 ( G ) x i &#175; = w i x i &#175; + ∑ j : j ~ i w i j x j &#175; ,</p><p>i.e.,</p><p>x i &#175; T ( q 1 ( G ) Ι t &#215; t − w i ) x i &#175; = ∑ j : j ~ i x i &#175; T w i j x j ≤ &#175; ∑ j : j ~ i | x i &#175; T w i j x j &#175; | .</p><p>From (7) and using Lemma 2, we get</p><p>≤ x i &#175; T x i &#175; ∑ j : j ~ i q 1 ( w i j ) .</p><p>From Lemma 1 and Lemma 3, we have</p><p>( q 1 ( G ) − q 1 ( w i ) ) x i &#175; T x i &#175; ≤ x i &#175; T ( q 1 ( G ) Ι t &#215;   t − w i ) x i &#175; ≤ x i &#175; T x i &#175;   q 1 ( w i ) .</p><p>Thus</p><p>q 1 ( G ) ≤ max i ∈ V { 2 q 1 ( w i ) } .</p><p>Hence the theorem follows.</p><p>Corollary 6.</p><p>Let G be a simple connected weighted graph where each edge weight w i j is a positive number. Then</p><p>q 1 ( G ) ≤ max i ∈ V { 2 w i } .</p><p>Proof.</p><p>For weighted graphs where the edge weights w i j are positive number, we have q 1 ( w i j ) = w i j and q 1 ( w i ) = w i , for all i ,   j . Using Theorem 5 we get the required result.</p><p>Corollary 7. [<xref ref-type="bibr" rid="scirp.83136-ref5">5</xref>] .</p><p>Let G be a simple connected unweighted graph. Then</p><p>q 1 ( G ) ≤ max i ∈ V { 2 d i } ,</p><p>where d i is the degree of vertex i.</p><p>Proof.</p><p>For an unweighted graph, w i j = 1 and w i = d i for all i ,   j and i ~ j . Using Corollary 6 we get the required result.</p><p>Theorem 8.</p><p>Let G be a simple connected weighted graph. Then</p><p>q 1 ( G ) ≤ max i ~ j { q 1 ( w i ) + ∑ k : k ~ j q 1 ( w j k ) } . (9)</p><p>Proof.</p><p>Let us consider the matrix M ( G ) = d i a g ( q 1 ( w 1 ) I t &#215; t , q 1 ( w 2 ) I t &#215; t , ⋯ ,   q 1 ( w n ) I t &#215; t ) . The ( i ,   j ) -th element of M ( G ) − 1 Q ( G ) M ( G ) is</p><p>{ w i ;                               if   i = j , q 1 ( w j ) q 1 ( w i ) w i j ;       if   i ~ j , 0 ;                             otherwise .</p><p>Let x &#175; = ( x 1 &#175; T ,   x 2 &#175; T , ⋯ ,   x n &#175; T ) T be an eigenvector corresponding to the eigenvalue q 1 ( G ) of M ( G ) − 1 Q ( G ) M ( G ) and x i &#175; be the vector component of x &#175; such that</p><p>x i &#175; T x i &#175; = max j ∈ V { x j &#175; T x j } &#175; . (10)</p><p>Since x &#175; is nonzero, so is x i &#175; . We have</p><p>{ M ( G ) − 1 Q ( G ) M ( G ) } x &#175; = q 1 ( G ) x &#175; . (11)</p><p>From the i-th Equation of (11), we get</p><p>q 1 ( G ) x i &#175; = w i x i &#175; + ∑ j : j ~ i q 1 ( w j ) q 1 ( w i ) w i j x j &#175; ,</p><p>i.e.,</p><p>x i &#175; T ( q 1 ( G ) Ι t &#215; t − w i ) x i &#175; ≤ ∑ j : j ~ i q 1 ( w j ) q 1 ( w i ) | x i &#175; T w i j x j &#175; | .</p><p>From (10) and using Lemma 1 and Lemma 2, we get</p><p>( q 1 ( G ) − q 1 ( w i ) ) x i &#175; T x i &#175; ≤ x i &#175; T ( q 1 ( G ) Ι t &#215; t − w i ) x i &#175; ≤ x i &#175; T x i &#175; ∑ j : j ~ i q 1 ( w j ) q 1 ( w i ) q 1 ( w i j ) ≤ x i &#175; T x i &#175; 1 q 1 ( w i ) max j : j ~ i { q 1 ( w j ) } ∑ j : j ~ i q 1 ( w i j )     . (12)</p><p>Thus</p><p>q 1 ( G ) ≤ max i ~ j { q 1 ( w i ) + ∑ k : k ~ j q 1 ( w j k ) } .</p><p>Hence the theorem follows.</p><p>Corollary 9.</p><p>Let G be a simple connected weighted graph where each edge weight w i j is a positive number. Then</p><p>q 1 ( G ) ≤ max i ~ j { w i + w j } .</p><p>Proof.</p><p>For weighted graphs where the edge weights w i j are positive number, we have q 1 ( w i j ) = w i j and q 1 ( w i ) = w i , for all i ,   j . Using Theorem 8 we get the required result.</p><p>Corollary 10. [<xref ref-type="bibr" rid="scirp.83136-ref6">6</xref>] .</p><p>Let G be a simple connected unweighted graph. Then</p><p>q 1 ( G ) ≤ max i ~ j { d i + d j } ,</p><p>where d i is the degree of vertex i.</p><p>Proof.</p><p>For an unweighted graph, w i j = 1 and w i = d i for all i ,   j and i ~ j . Using Corollary 9 we get the required result.</p><p>Theorem 11.</p><p>Let G be a simple connected weighted graph. Then,</p><p>q 1 ( G ) ≤ max i ~ j { q 1 ( w i ) + γ i } , (13)</p><p>where γ i = ∑ j : j ~ i q 1 ( w i j ) q 1 ( w j ) q 1 ( w i ) .</p><p>Proof.</p><p>From (12), we get</p><p>q 1 ( G ) ≤ q 1 ( w i ) + ∑ j : j ~ i q 1 ( w j ) q 1 ( w i ) q 1 ( w i j ) ≤ max i ∈ V { q 1 ( w i ) + γ i } .</p><p>The proof is complete.</p><p>Corollary 12.</p><p>Let G be a simple connected weighted graph where each edge weight <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x116.png" xlink:type="simple"/></inline-formula> is a positive number. Then</p><p><inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x117.png" xlink:type="simple"/></inline-formula>,</p><p>where<inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x118.png" xlink:type="simple"/></inline-formula>.</p><p>Proof.</p><p>For weighted graphs where the edge weights <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x119.png" xlink:type="simple"/></inline-formula> are positive number, we have <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x120.png" xlink:type="simple"/></inline-formula> and<inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x121.png" xlink:type="simple"/></inline-formula>, for all<inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x122.png" xlink:type="simple"/></inline-formula>. Using Theorem 11 we get the required result.</p><p>Corollary 13. [<xref ref-type="bibr" rid="scirp.83136-ref6">6</xref>] .</p><p>Let G be a simple connected unweighted graph. Then</p><p><inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x123.png" xlink:type="simple"/></inline-formula>,</p><p>where <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x124.png" xlink:type="simple"/></inline-formula> is the degree of vertex i and <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x125.png" xlink:type="simple"/></inline-formula> is the average of the degrees of the vertices adjacent to vertex i.</p><p>Proof.</p><p>For an unweighted graph, <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x126.png" xlink:type="simple"/></inline-formula>and <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x127.png" xlink:type="simple"/></inline-formula> for all <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x128.png" xlink:type="simple"/></inline-formula> and<inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x129.png" xlink:type="simple"/></inline-formula>. Using Corollary 12 we get the required result.</p><p>Theorem 14.</p><p>Let G be a simple connected weighted graph. Then</p><disp-formula id="scirp.83136-formula3"><label>, (14)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x130.png"  xlink:type="simple"/></disp-formula><p>where <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x131.png" xlink:type="simple"/></inline-formula></p><p>Proof.</p><p>Let <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x132.png" xlink:type="simple"/></inline-formula> be an eigenvector corresponding to the eigenvalue<inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x133.png" xlink:type="simple"/></inline-formula>. We assume that <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x133.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x134.png" xlink:type="simple"/></inline-formula> be the vector component of <inline-formula><inline-graphic xlink:href="/html.scirp.org/file/6-2230150x133.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x134.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x135.png" xlink:type="simple"/></inline-formula> such that</p><disp-formula id="scirp.83136-formula4"><label>. (15)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x136.png"  xlink:type="simple"/></disp-formula><p>Since <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x137.png" xlink:type="simple"/></inline-formula> is nonzero, so is<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x137.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x138.png" xlink:type="simple"/></inline-formula>. We have</p><disp-formula id="scirp.83136-formula5"><graphic  xlink:href="//html.scirp.org/file/6-2230150x139.png"  xlink:type="simple"/></disp-formula><p>In order to prove the Inequality (14), we consider a simple quadratic function of<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x140.png" xlink:type="simple"/></inline-formula>:</p><disp-formula id="scirp.83136-formula6"><label>(16)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x141.png"  xlink:type="simple"/></disp-formula><p>From the i-th Equation of (16), we get</p><disp-formula id="scirp.83136-formula7"><graphic  xlink:href="//html.scirp.org/file/6-2230150x142.png"  xlink:type="simple"/></disp-formula><p>i.e.,</p><disp-formula id="scirp.83136-formula8"><graphic  xlink:href="//html.scirp.org/file/6-2230150x143.png"  xlink:type="simple"/></disp-formula><p>Since <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x144.png" xlink:type="simple"/></inline-formula> is the positive definite matrix of edge ij, <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x144.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x145.png" xlink:type="simple"/></inline-formula>matrix is also positive definite. From Lemma 1, we have</p><disp-formula id="scirp.83136-formula9"><label>(17)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x146.png"  xlink:type="simple"/></disp-formula><p>Four cases arise;</p><p>1) <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x147.png" xlink:type="simple"/></inline-formula>and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x147.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x148.png" xlink:type="simple"/></inline-formula> are real symmetric matrices for all j, j∼i and for all k, k∼j, j∼i.</p><p>2) <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x149.png" xlink:type="simple"/></inline-formula>is a real symmetric matrix for all j, j∼i and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x149.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x150.png" xlink:type="simple"/></inline-formula> is not a real symmetric matrix for all k, k∼j, j∼i.</p><p>3) <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x151.png" xlink:type="simple"/></inline-formula>is not a real symmetric matrix for all j, j∼i and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x151.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x152.png" xlink:type="simple"/></inline-formula> is a real symmetric matrix for all k, k∼j, j∼i.</p><p>4) <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x153.png" xlink:type="simple"/></inline-formula>and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x153.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x154.png" xlink:type="simple"/></inline-formula> are not real symmetric matrices for all j, j∼i and for all k, k∼j, j∼i.</p><p>From (15), (17) and using Lemma 2 and Lemma 4, we get</p><disp-formula id="scirp.83136-formula10"><label>(18)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x155.png"  xlink:type="simple"/></disp-formula><p>for Case (1), Case (2), Case (3) and Case (4). Hence,</p><disp-formula id="scirp.83136-formula11"><graphic  xlink:href="//html.scirp.org/file/6-2230150x156.png"  xlink:type="simple"/></disp-formula><p>From Lemma 3, we have</p><disp-formula id="scirp.83136-formula12"><graphic  xlink:href="//html.scirp.org/file/6-2230150x157.png"  xlink:type="simple"/></disp-formula><p>i.e.,</p><disp-formula id="scirp.83136-formula13"><graphic  xlink:href="//html.scirp.org/file/6-2230150x158.png"  xlink:type="simple"/></disp-formula><p>Thus</p><disp-formula id="scirp.83136-formula14"><graphic  xlink:href="//html.scirp.org/file/6-2230150x159.png"  xlink:type="simple"/></disp-formula><p>From the inequality above, for every different value to b, we can get several distinct upper bounds. In particular, if<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x160.png" xlink:type="simple"/></inline-formula>, we get</p><p><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x161.png" xlink:type="simple"/></inline-formula>.</p><p>This completes the proof.</p><p>Corollary 15.</p><p>Let G be a simple connected weighted graph where each edge weight <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x162.png" xlink:type="simple"/></inline-formula> is a positive number. Then</p><p><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x163.png" xlink:type="simple"/></inline-formula>,</p><p>where<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x164.png" xlink:type="simple"/></inline-formula>.</p><p>Proof.</p><p>For weighted graphs where the edge weights <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x165.png" xlink:type="simple"/></inline-formula> are positive number, we have <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x165.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x166.png" xlink:type="simple"/></inline-formula> and<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x165.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x166.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x167.png" xlink:type="simple"/></inline-formula>, for all<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x165.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x166.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x167.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x168.png" xlink:type="simple"/></inline-formula>. Using Theorem 14 we get the required result.</p><p>Corollary 16. [<xref ref-type="bibr" rid="scirp.83136-ref5">5</xref>] .</p><p>Let G be a simple connected unweighted graph. Then</p><p><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x169.png" xlink:type="simple"/></inline-formula>,</p><p>where <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x170.png" xlink:type="simple"/></inline-formula> is the degree of vertex i and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x170.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x171.png" xlink:type="simple"/></inline-formula> is the average of the degrees of the vertices adjacent to vertex i.</p><p>Proof.</p><p>For an unweighted graph, <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x172.png" xlink:type="simple"/></inline-formula>and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x172.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x173.png" xlink:type="simple"/></inline-formula> for all <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x172.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x173.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x174.png" xlink:type="simple"/></inline-formula> and<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x172.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x173.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x174.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x175.png" xlink:type="simple"/></inline-formula>. Using Corollary 15 we get the required result.</p><p>Theorem 17.</p><p>Let G be a simple connected weighted graph. Then,</p><disp-formula id="scirp.83136-formula15"><label>, (19)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x176.png"  xlink:type="simple"/></disp-formula><p>where <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x177.png" xlink:type="simple"/></inline-formula></p><p>Proof.</p><p><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x178.png" xlink:type="simple"/></inline-formula>. The <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x178.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x179.png" xlink:type="simple"/></inline-formula>-th element of <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x178.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x179.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x180.png" xlink:type="simple"/></inline-formula> is</p><disp-formula id="scirp.83136-formula16"><graphic  xlink:href="//html.scirp.org/file/6-2230150x181.png"  xlink:type="simple"/></disp-formula><p>Let <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x182.png" xlink:type="simple"/></inline-formula> be an eigenvector corresponding to the eigenvalue <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x182.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x183.png" xlink:type="simple"/></inline-formula> of<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x182.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x183.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x184.png" xlink:type="simple"/></inline-formula>, <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x182.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x183.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x184.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x185.png" xlink:type="simple"/></inline-formula>and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x182.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x183.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x184.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x185.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x186.png" xlink:type="simple"/></inline-formula> are the vector components of <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x182.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x183.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x184.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x185.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x186.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x187.png" xlink:type="simple"/></inline-formula> such that</p><disp-formula id="scirp.83136-formula17"><label>, (20)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x188.png"  xlink:type="simple"/></disp-formula><disp-formula id="scirp.83136-formula18"><label>. (21)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x189.png"  xlink:type="simple"/></disp-formula><p>Since <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x190.png" xlink:type="simple"/></inline-formula> is nonzero, so is<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x190.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x191.png" xlink:type="simple"/></inline-formula>. We have</p><disp-formula id="scirp.83136-formula19"><label>. (22)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x192.png"  xlink:type="simple"/></disp-formula><p>From the i-th Equation of (22), we get</p><p><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x193.png" xlink:type="simple"/></inline-formula>.</p><p>From Lemma 2, we get</p><disp-formula id="scirp.83136-formula20"><label>. (23)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x194.png"  xlink:type="simple"/></disp-formula><p>From (21), (23) and using Lemma 1, we get</p><disp-formula id="scirp.83136-formula21"><label>(24)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x195.png"  xlink:type="simple"/></disp-formula><p>Similarly, from the j-th Equation of (22), we have</p><disp-formula id="scirp.83136-formula22"><label>(25)</label><graphic position="anchor" xlink:href="//html.scirp.org/file/6-2230150x196.png"  xlink:type="simple"/></disp-formula><p>From (24) and (25), we get</p><disp-formula id="scirp.83136-formula23"><graphic  xlink:href="//html.scirp.org/file/6-2230150x197.png"  xlink:type="simple"/></disp-formula><p>Thus</p><p><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x198.png" xlink:type="simple"/></inline-formula>.</p><p>Hence the theorem is proved.</p><p>Corollary 18.</p><p>Let G be a simple connected weighted graph where each edge weight <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x199.png" xlink:type="simple"/></inline-formula> is a positive number. Then</p><p><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x200.png" xlink:type="simple"/></inline-formula>,</p><p>where<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x201.png" xlink:type="simple"/></inline-formula>.</p><p>Proof.</p><p>For weighted graphs where the edge weights <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x202.png" xlink:type="simple"/></inline-formula> are positive number, we have <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x202.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x203.png" xlink:type="simple"/></inline-formula> and<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x202.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x203.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x204.png" xlink:type="simple"/></inline-formula>, for all<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x202.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x203.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x204.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x205.png" xlink:type="simple"/></inline-formula>. Using Theorem 17 we get the required result.</p><p>Corollary 19. [<xref ref-type="bibr" rid="scirp.83136-ref7">7</xref>] .</p><p>Let G be a simple connected unweighted graph. Then</p><p><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x206.png" xlink:type="simple"/></inline-formula>,</p><p>where <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x207.png" xlink:type="simple"/></inline-formula> is the degree of vertex i and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x207.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x208.png" xlink:type="simple"/></inline-formula> is the average of the degrees of the vertices adjacent to vertex i.</p><p>Proof.</p><p>For an unweighted graph, <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x209.png" xlink:type="simple"/></inline-formula>and <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x209.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x210.png" xlink:type="simple"/></inline-formula> for all <inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x209.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x210.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x211.png" xlink:type="simple"/></inline-formula> and<inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x209.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x210.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x211.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="//html.scirp.org/file/6-2230150x212.png" xlink:type="simple"/></inline-formula>. Using Corollary 18 we get the required result.</p></sec><sec id="s3"><title>Conflict of Interests</title><p>The authors declare that there is no conlict of interests regarding the publication of this paper.</p></sec><sec id="s4"><title>Cite this paper</title><p>B&#252;y&#252;kk&#246;se, Ş., Mutlu, N. and G&#246;k, G.K. (2018) A Note on the Spectral Radius of Weighted Signless Laplacian Matrix. Advances in Linear Algebra &amp; Matrix Theory, 8, 53-63. https://doi.org/10.4236/alamt.2018.81006</p></sec></body><back><ref-list><title>References</title><ref id="scirp.83136-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Zhang, F. (1999) Matrix Theory: Basic Results and Techniques. Springer-Verlag, New York. https://doi.org/10.1007/978-1-4757-5797-2</mixed-citation></ref><ref id="scirp.83136-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Horn, R.A. and Johnson, C.R. (1985) Matrix Analysis. 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