Estrada Index of Benzenoid Hydrocarbons
|
|
- Jasmin Melton
- 5 years ago
- Views:
Transcription
1 Estrada Idex of Bezeoid Hydrocarbos Iva Gutma ad Slavko Radeković Faculty of Sciece Uiversity of Kragujevac P. O. Box Kragujevac Serbia Reprit requests to Prof. I. G.; Fax: ; Z. Naturforsch. 62a (2007); received December A structure-descriptor EE recetly proposed by Estrada is examied. If λ 1 λ 2...λ are the eigevalues of the molecular graph the EE = e λ i. I the case of bezeoid hydrocarbos with carbo atoms ad m carbo-carbo ( bods EE is foud to be accurately approximated by meas of / ) the formula a 1 cosh +a 2 wherea ad a 2 = 0.64 are empirically determied fittig costats. Withi classes of bezeoid isomers (which all have equal ad m) the Estrada idex is liearly proportioal to the umber of bay regios. Key words: Estrada Idex; Bezeoid Hydrocarbos; Molecular Graph; Spectrum (of Graph). 1. Itroductio I this paper we are cocered with a molecular structure-descriptor of bezeoid hydrocarbos that we refer to as the Estrada idex. Itisdefiedasfollows. Let G be the molecular graph of a bezeoid hydrocarbo [1 5]. Let ad m be respectively the umber of vertices ad edges of G. The the formula of the uderlyig hydrocarbo is C H 3 ad must be eve [3 5]. The eigevalues λ 1 λ 2...λ of the adjacecy matrix of G are said to be the eigevalues of G adtoform the spectrum of G. These will be labelled so that λ 1 λ 2 λ. The basic properties of graph eigevalues ca be foud i [6]. The Estrada idex is defied as EE = EE(G)= e λ i. (1) Although itroduced quite recetly [7] the Estrada idex has already foud umerous applicatios. It was used to quatify the degree of foldig of logchai molecules especially proteis [7 9]. Aother fully urelated applicatio of EE was put forward by Estrada ad Rodríguez-Velázquez [10 11]. They showed that EE provides a measure of the average cetrality of complex (commuicatio social metabolic etc.) etworks. I additio to this i a recet work [12] a coectio betwee EE ad the cocept of exteded atomic brachig was suggested. Util ow oly some straightforward mathematical properties of the Estrada idex were established [ ] but its depedece o molecular structure has ot bee ivestigated. The preset paper is aimed at cotributig towards fillig this gap. I what follows we use the fuctios hyperbolic cosie ad hyperbolic sie defied as usual as cosh(x)= ex + e x ad sih(x)= ex e x 2 2 respectively. Our startig poits are the well kow relatios for the eigevalues of bezeoid graphs [2 6] λ i + λ +1 i fori = (2) kow as the pairig theorem [ ] ad /2 (λ i ) 2 = m. (3) Because of (2) half of the eigevalues of a bezeoid graph G are positive (or zero) ad the other half egative (or zero) implyig [11] /2 EE(G)=2 cosh(λ i ) / 07 / $ c 2007 Verlag der Zeitschrift für Naturforschug Tübige
2 I. Gutma ad S. Radeković Estrada Idex of Bezeoid Hydrocarbos A McClellad-Type Boud for the Estrada Idex The method by which a boud EE for EE is deduced i this sectio is fully aalogous to a method used log time ago [16] for estimatig the total π- electro eergy E. I the otatio specified above for a bezeoid graph G /2 E = E(G)=2 λ i. (4) For a fixed value of m i. e. assumig that coditio (3) is obeyed a extremal value E of E is obtaied by employig the Lagrage multiplier techique: A auxiliary fuctio F is costructed as /2 F := 2 λ i α ad the coditio ) (λ i ) 2 m ( /2 F imposed for all k = 12.../2. This leads to 2 2αλ k i. e. λ k = α which combied with (3) yields λ k = for k = 12.../2 ad substituted back ito (4) results i E =. This is just the famous McClellad upper boud for total π-electro eergy [17 19]. Applyig a aalogous reasoig we costruct the auxiliary fuctio /2 FF := 2 cosh(λ i ) α ad impose ) (λ i ) 2 m ( /2 FF for k = 12.../2. This results i 2sih(λ k ) 2αλ k. It is easily see that for α > 0 the equatio sih(x) α x has a sigle positive-valued solutio. Deote it by.theα = sih( )/. Now from λ k = for k = 12.../2 adrelatio (3) we readily obtai = ad therefore EE = cosh ( ). (5) Note that / is the average vertex degree of the graph G. Therefore for bezeoid graphs / > 2 ad thus > 2. Curiously however i cotrast to E which is a upper boud for the total π-electro eergy [17] the estimate EE formula (5) is a lower boud for the Estrada idex. To see this we examie the Hessia matrix H(FF) of the fuctio FF. Because of FF = 2sih(λ k ) 2αλ k oe has 2 FF λk 2 = 2cosh(λ k ) 2α ad 2 FF λ k for k k. Therefore H(FF) is a diagoal matrix whose all diagoal elemets are equal to 2cosh( ) 2α i. e. 2 cosh( ) 2 sih(). Now 2cosh( ) 2 sih() = ( 1)e +( + 1)e which for > 2 is evidetly positive-valued. Thus all eigevalues of H(FF) are positive-valued ad cosequetly the extremal value EE is a miimum. We thus proved:
3 256 I. Gutma ad S. Radeković Estrada Idex of Bezeoid Hydrocarbos EE = a 1 EE + a 2 (6) a 1 = ± a 2 = 0.64 ± 0.08 with a remarkably high correlatio coefficiet I the sample examied the average relative error of the approximatio (6) is 0.19% ad the maximal observed relative error 0.83%. Oe evidet coclusio from the above result is that the gross part of the Estrada idices of bezeoid systems is determied by the parameters ad m.iother words the Estrada idices of bezeoid isomers differ very little. I the subsequet sectio we examie these small differeces of the EE values of isomeric bezeoids ad try to see which is the mai structural feature that is resposible for them. 4. O Estrada Idices of Bezeoid Isomers Expadig the fuctio e x ito a power series ad usig the defiitio (1) of the Estrada idex oe readily arrives at [7 10] Fig. 1. The Estrada idices (EE) of the 106 bezeoid hydrocarbos from [22] plotted versus their lower boud EE accordig to (5). For details see text. Theorem 1. The Estrada idex of a bezeoid hydrocarbo with carbo atoms ad m carbo-carbo bods is always greater tha cosh( /). 3. A (m m)-type Approximatio for the Estrada Idex The McClellad upper boud E for a total π- electro eergy E provides a excellet approximate formula for E of cojugated molecules [17] of the form E a 1 E +a 2. I fact i the case of bezeoid hydrocarbos this formula with a ad a 2.45 happes to be the best (m)-type approximatio for E [20 21]. I view of this we examied how well a expressio of the form a 1 EE + a 2 would approximate the Estrada idex. The quality of this approximatio is see i Figure 1. Ideed the correlatio betwee EE ad EE is almost perfectly liear. Least-squares fittig usig the stadard data set of 106 Kekuléa bezeoid hydrocarbos from [22] (same as employed i [20 21] ad elsewhere [23 24]) yields the regressio lie EE(G)= k 0 M k (G) k! where M k is the k-th spectral momet of the molecular graph G M k = M k (G)= (λ i ) k. For all graphs M 0 = M 1 ad M 2 = [2 6]. For all bipartite graphs (ad thus also for the molecular graphs of bezeoid hydrocarbos) M k for odd k. We thus have EE(G)=+m M M M 8 + (7) which implies EE(G) + m M M 6. (8) The depedece of the first few eve spectral momets of bezeoid hydrocarbos o the molecular structure is kow [25 27]. I particular M 4 (G)=18m 12 M 6 (G)=158m b where b is the umber of bay regios [ ]. Whe these are substituted back ito (7) ad (8) we obtai EE(G)= 1 (1418m b) higher order terms
4 I. Gutma ad S. Radeković Estrada Idex of Bezeoid Hydrocarbos 257 Table 1. Statistical data for correlatios of the form EE = a 1 b + a 2 for sets of bezeoid isomers with carbo atoms ad m carbo-carbo bods; b is the umber of bay regios. All sets cosidered cotai all possible isomers equal to N.I. The respective correlatio coefficiet is R. m N.I. a 1 a 2 R ± ± ± ± ± ± ± ± ± ± Fig. 2. The Estrada idices (EE) of the 36 bezeoid isomers with the formula C 26 H 16 plotted versus their umber of bay regios (b). For details see Table 1 ad text. i. e. EE(G) 1 (1418m b). (9) 720 [1] N. Triajstić Chemical Graph Theory CRC Boca Rato [2] I. Gutma ad O. E. Polasky Mathematical Cocepts i Orgaic Chemistry Spriger-Verlag Berli [3] I. Gutma ad S. J. Cyvi Itroductio to the Theory of Bezeoid Hydrocarbos Spriger-Verlag Berli [4] M. Zader Z. Naturforsch. 45a 1041 (1990). [5] M. Zader Topics Curr. Chem (1990). [6] D. Cvetković M. Doob ad H. Sachs Spectra of Graphs Theory ad Applicatio Academic Press New York [7] E. Estrada Chem. Phys. Lett (2000). [8] E. Estrada Bioiformatics (2002). [9] E. Estrada Proteis (2004). [10] E. Estrada ad J. A. Rodríguez-Velázquez Phys. Rev. 71E (2005). Accordig to the approximatio (9) withi classes of isomeric bezeoids the Estrada idex is a icreasig liear fuctio of the parameter b ad the slope of the respective lie is (almost) idepedet of ad m ad (early) equal to 1/ That this is ideed the case is see from Fig. 2 ad from the data give i Table Cocludig Remarks We deem to have established the mai structural features of bezeoid hydrocarbos that determie the value of their Estrada idices. These are first of all the parameters ad m that are capable of reproducig some 99.8% of EE. The(m)-type approximatio a 1 EE +a 2 with EE beig give by (5) is maybe ot the best possible but is remarkably accurate. The quality of the liear relatio betwee EE ad EE is illustrated by Figure 1. Ayway the Estrada idices of bezeoid isomers (i. e. species havig equal values of ad m) vary oly to a very limited extet. The mai structural feature ifluecig these variatios is the umber b of bay regios. Withi sets of bezeoid isomers EE is a icreasig liear fuctio of b. The slope of this fuctio is practically idepedet of ad m (as see from the data for a 1 i Table 1). It is close yet ot equal to the slope predicted by meas of a trucated expasio of EE i terms of spectral momets. We dare to coclude that the structure depedece of the Estrada idices of bezeoid hydrocarbos is ow almost completely uderstood. [11] E. Estrada ad J. A. Rodríguez-Velázquez Phys. Rev. 72E (2005). [12] E. Estrada J. A. Rodríguez-Velázquez ad M. Radić It. J. Quatum Chem (2006). [13] I. Gutma E. Estrada ad J. A. Rodríguez-Velázquez Croat. Chem. Acta 79 (i press). [14] I. Gutma Z. Naturforsch. 39a 152 (1984). [15] R. B. Mallio ad D. H. Rouvray J. Math. Chem. 5 1 (1990). [16] I. Gutma MATCH Commu. Math. Comput. Chem (1983). [17] B. J. McClellad J. Chem. Phys (1971). [18] A. Graovac I. Gutma P. E. Joh D. Vidović ad I. Vlah Z. Naturforsch. 56a 307 (2001). [19] H. Fripertiger I. Gutma A. Kerber A. Kohert ad D. Vidović Z. Naturforsch. 56a 342 (2001). [20] I. Gutma Topics Curr. Chem (1992).
5 258 I. Gutma ad S. Radeković Estrada Idex of Bezeoid Hydrocarbos [21] I. Gutma ad T. Soldatović MATCH Commu. Math. Comput. Chem (2001). [22] R. Zahradik ad J. Pacir HMO Eergy Characteristics Pleum Press New York [23] J. Cioslowski ad I. Gutma Z. Naturforsch. 41a 861 (1986). [24] I. Gutma J. H. Koole V. Moulto M. Parac T. Soldatović ad D. Vidović Z.Naturforsch.55a 507 (2000). [25] J. Cioslowski Z. Naturforsch. 40a 1167 (1985). [26] G. G. Hall Theor. Chim. Acta (1986). [27] S. Marković ad I. Gutma J. Mol. Struct. (Theochem.) (1991).
The McClelland approximation and the distribution of -electron molecular orbital energy levels
J. Serb. Chem. Soc. 7 (10) 967 973 (007) UDC 54 74+537.87:53.74+539.194 JSCS 369 Origial scietific paper The McClellad approximatio ad the distributio of -electro molecular orbital eergy levels IVAN GUTMAN*
More informationResolvent Estrada Index of Cycles and Paths
SCIENTIFIC PUBLICATIONS OF THE STATE UNIVERSITY OF NOVI PAZAR SER. A: APPL. MATH. INFORM. AND MECH. vol. 8, 1 (216), 1-1. Resolvet Estrada Idex of Cycles ad Paths Bo Deg, Shouzhog Wag, Iva Gutma Abstract:
More informationMORE GRAPHS WHOSE ENERGY EXCEEDS THE NUMBER OF VERTICES
Iraia Joural of Mathematical Scieces ad Iformatics Vol. 2, No. 2 (2007), pp 57-62 MORE GRAPHS WHOSE ENERGY EXCEEDS THE NUMBER OF VERTICES CHANDRASHEKAR ADIGA, ZEYNAB KHOSHBAKHT ad IVAN GUTMAN 1 DEPARTMENT
More informationLaplacian energy of a graph
Liear Algebra ad its Applicatios 414 (2006) 29 37 www.elsevier.com/locate/laa Laplacia eergy of a graph Iva Gutma a,, Bo Zhou b a Faculty of Sciece, Uiversity of Kragujevac, 34000 Kragujevac, P.O. Box
More informationLAPLACIAN ENERGY OF GENERALIZED COMPLEMENTS OF A GRAPH
Kragujevac Joural of Mathematics Volume 4 018, Pages 99 315 LAPLACIAN ENERGY OF GENERALIZED COMPLEMENTS OF A GRAPH H J GOWTHAM 1, SABITHA D SOUZA 1, AND PRADEEP G BHAT 1 Abstract Let P = {V 1, V, V 3,,
More informationBOUNDS FOR THE DISTANCE ENERGY OF A GRAPH
59 Kragujevac J. Math. 31 (2008) 59 68. BOUNDS FOR THE DISTANCE ENERGY OF A GRAPH Harishchadra S. Ramae 1, Deepak S. Revakar 1, Iva Gutma 2, Siddai Bhaskara Rao 3, B. Devadas Acharya 4 ad Haumappa B. Walikar
More informationON BANHATTI AND ZAGREB INDICES
JOURNAL OF THE INTERNATIONAL MATHEMATICAL VIRTUAL INSTITUTE ISSN (p) 2303-4866, ISSN (o) 2303-4947 www.imvibl.org /JOURNALS / JOURNAL Vol. 7(2017), 53-67 DOI: 10.7251/JIMVI1701053G Former BULLETIN OF THE
More informationSymmetric Division Deg Energy of a Graph
Turkish Joural of Aalysis ad Number Theory, 7, Vol, No 6, -9 Available olie at http://pubssciepubcom/tat//6/ Sciece ad Educatio Publishig DOI:69/tat--6- Symmetric Divisio Deg Eergy of a Graph K N Prakasha,
More informationMalaya J. Mat. 4(3)(2016) Reciprocal Graphs
Malaya J Mat 43)06) 380 387 Reciprocal Graphs G Idulal a, ad AVijayakumar b a Departmet of Mathematics, StAloysius College, Edathua, Alappuzha - 689573, Idia b Departmet of Mathematics, Cochi Uiversity
More informationNew Bounds for the Resolvent Energy of Graphs
SCIENTIFIC PUBLICATIONS OF THE STATE UNIVERSITY OF NOVI PAZAR SER A: APPL MATH INFORM AND MECH vol 9, 2 207), 87-9 New Bouds for the Resolvet Eergy of Graphs E H Zogić, E R Glogić Abstract: The resolvet
More informationMiskolc Mathematical Notes HU e-issn Bounds for Laplacian-type graph energies. Ivan Gutman, Emina Milovanovic, and Igor Milovanovic
Miskolc Mathematical Notes HU e-issn 787-43 Vol. 6 (05), No, pp. 95-03 DOI: 0.854/MMN.05.40 Bouds for Laplacia-type graph eergies Iva Gutma, Emia Milovaovic, ad Igor Milovaovic Miskolc Mathematical Notes
More informationInfinite Sequences and Series
Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet
More informationSome inequalities for the Kirchhoff index of graphs
Malaya Joural of Matematik Vol 6 No 349-353 08 https://doiorg/06637/mjm060/0008 Some iequalities for the Kirchhoff idex of graphs Igor Milovaovic * Emia Milovaovic Marja Matejic ad Edi Glogic Abstract
More informationPI Polynomial of V-Phenylenic Nanotubes and Nanotori
It J Mol Sci 008, 9, 9-34 Full Research Paper Iteratioal Joural of Molecular Scieces ISSN 4-0067 008 by MDPI http://wwwmdpiorg/ijms PI Polyomial of V-Pheyleic Naotubes ad Naotori Vahid Alamia, Amir Bahrami,*
More informationLaplacian Minimum covering Randić Energy of a Graph
Commuicatios i Mathematics ad Applicatios Vol 9 No pp 67 88 8 ISSN 975-867 (olie); 976-595 (prit) Published by RGN Publicatios http://wwwrgpublicatioscom Laplacia Miimum coverig Radić Eergy of a Graph
More information6.3 Testing Series With Positive Terms
6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial
More informationLinear Regression Demystified
Liear Regressio Demystified Liear regressio is a importat subject i statistics. I elemetary statistics courses, formulae related to liear regressio are ofte stated without derivatio. This ote iteds to
More informationZeros of Polynomials
Math 160 www.timetodare.com 4.5 4.6 Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered with fidig the solutios of polyomial equatios of ay degree
More informationRiesz-Fischer Sequences and Lower Frame Bounds
Zeitschrift für Aalysis ud ihre Aweduge Joural for Aalysis ad its Applicatios Volume 1 (00), No., 305 314 Riesz-Fischer Sequeces ad Lower Frame Bouds P. Casazza, O. Christese, S. Li ad A. Lider Abstract.
More information1 Adiabatic and diabatic representations
1 Adiabatic ad diabatic represetatios 1.1 Bor-Oppeheimer approximatio The time-idepedet Schrödiger equatio for both electroic ad uclear degrees of freedom is Ĥ Ψ(r, R) = E Ψ(r, R), (1) where the full molecular
More informationNew Version of the Rayleigh Schrödinger Perturbation Theory: Examples
New Versio of the Rayleigh Schrödiger Perturbatio Theory: Examples MILOŠ KALHOUS, 1 L. SKÁLA, 1 J. ZAMASTIL, 1 J. ČÍŽEK 2 1 Charles Uiversity, Faculty of Mathematics Physics, Ke Karlovu 3, 12116 Prague
More information1 Inferential Methods for Correlation and Regression Analysis
1 Iferetial Methods for Correlatio ad Regressio Aalysis I the chapter o Correlatio ad Regressio Aalysis tools for describig bivariate cotiuous data were itroduced. The sample Pearso Correlatio Coefficiet
More informationA collocation method for singular integral equations with cosecant kernel via Semi-trigonometric interpolation
Iteratioal Joural of Mathematics Research. ISSN 0976-5840 Volume 9 Number 1 (017) pp. 45-51 Iteratioal Research Publicatio House http://www.irphouse.com A collocatio method for sigular itegral equatios
More informationThe Riemann Zeta Function
Physics 6A Witer 6 The Riema Zeta Fuctio I this ote, I will sketch some of the mai properties of the Riema zeta fuctio, ζ(x). For x >, we defie ζ(x) =, x >. () x = For x, this sum diverges. However, we
More informationThe Multiplicative Zagreb Indices of Products of Graphs
Iteratioal Joural of Mathematics Research. ISSN 0976-5840 Volume 8, Number (06), pp. 6-69 Iteratioal Research Publicatio House http://www.irphouse.com The Multiplicative Zagreb Idices of Products of Graphs
More informationR Index of Some Graphs
Aals of Pure ad Applied athematics Vol 6, No, 08, 6-67 IN: 79-087X P), 79-0888olie) Published o Jauary 08 wwwresearchmathsciorg DOI: http://dxdoiorg/0457/apam6a8 Aals of Departmet of athematicseethalakshmi
More informationrespectively. The Estrada index of the graph G is defined
Askari et al. Joural of Iequalities ad Applicatios (016) 016:10 DOI 10.1186/s13660-016-1061-9 RESEARCH Ope Access Seidel-Estrada idex Jalal Askari1, Ali Iramaesh1* ad Kikar Ch Das * Correspodece: iramaesh@modares.ac.ir
More informationDisjoint unions of complete graphs characterized by their Laplacian spectrum
Electroic Joural of Liear Algebra Volume 18 Volume 18 (009) Article 56 009 Disjoit uios of complete graphs characterized by their Laplacia spectrum Romai Boulet boulet@uiv-tlse.fr Follow this ad additioal
More informationMath 155 (Lecture 3)
Math 55 (Lecture 3) September 8, I this lecture, we ll cosider the aswer to oe of the most basic coutig problems i combiatorics Questio How may ways are there to choose a -elemet subset of the set {,,,
More informationSummary: CORRELATION & LINEAR REGRESSION. GC. Students are advised to refer to lecture notes for the GC operations to obtain scatter diagram.
Key Cocepts: 1) Sketchig of scatter diagram The scatter diagram of bivariate (i.e. cotaiig two variables) data ca be easily obtaied usig GC. Studets are advised to refer to lecture otes for the GC operatios
More information(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3
MATH 337 Sequeces Dr. Neal, WKU Let X be a metric space with distace fuctio d. We shall defie the geeral cocept of sequece ad limit i a metric space, the apply the results i particular to some special
More information62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +
62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of
More informationA NEW CLASS OF 2-STEP RATIONAL MULTISTEP METHODS
Jural Karya Asli Loreka Ahli Matematik Vol. No. (010) page 6-9. Jural Karya Asli Loreka Ahli Matematik A NEW CLASS OF -STEP RATIONAL MULTISTEP METHODS 1 Nazeeruddi Yaacob Teh Yua Yig Norma Alias 1 Departmet
More informationMath 61CM - Solutions to homework 3
Math 6CM - Solutios to homework 3 Cédric De Groote October 2 th, 208 Problem : Let F be a field, m 0 a fixed oegative iteger ad let V = {a 0 + a x + + a m x m a 0,, a m F} be the vector space cosistig
More informationTEACHER CERTIFICATION STUDY GUIDE
COMPETENCY 1. ALGEBRA SKILL 1.1 1.1a. ALGEBRAIC STRUCTURES Kow why the real ad complex umbers are each a field, ad that particular rigs are ot fields (e.g., itegers, polyomial rigs, matrix rigs) Algebra
More informationTopic 9: Sampling Distributions of Estimators
Topic 9: Samplig Distributios of Estimators Course 003, 2016 Page 0 Samplig distributios of estimators Sice our estimators are statistics (particular fuctios of radom variables), their distributio ca be
More informationWorksheet 23 ( ) Introduction to Simple Linear Regression (continued)
Worksheet 3 ( 11.5-11.8) Itroductio to Simple Liear Regressio (cotiued) This worksheet is a cotiuatio of Discussio Sheet 3; please complete that discussio sheet first if you have ot already doe so. This
More informationa b c d e f g h Supplementary Information
Supplemetary Iformatio a b c d e f g h Supplemetary Figure S STM images show that Dark patters are frequetly preset ad ted to accumulate. (a) mv, pa, m ; (b) mv, pa, m ; (c) mv, pa, m ; (d) mv, pa, m ;
More informationTo the use of Sellmeier formula
To the use of Sellmeier formula by Volkmar Brücker Seior Experte Service (SES) Bo ad HfT Leipzig, Germay Abstract Based o dispersio of pure silica we proposed a geeral Sellmeier formula for various dopats
More informationBounds of Balanced Laplacian Energy of a Complete Bipartite Graph
Iteratioal Joural of Computatioal Itelligece Research ISSN 0973-1873 Volume 13, Number 5 (2017), pp. 1157-1165 Research Idia Publicatios http://www.ripublicatio.com Bouds of Balaced Laplacia Eergy of a
More informationRandom Matrices with Blocks of Intermediate Scale Strongly Correlated Band Matrices
Radom Matrices with Blocks of Itermediate Scale Strogly Correlated Bad Matrices Jiayi Tog Advisor: Dr. Todd Kemp May 30, 07 Departmet of Mathematics Uiversity of Califoria, Sa Diego Cotets Itroductio Notatio
More informationEnergy of a Hypercube and its Complement
Iteratioal Joural of Algebra, Vol. 6, 01, o. 16, 799-805 Eergy of a Hypercube ad its Complemet Xiaoge Che School of Iformatio Sciece ad Techology, Zhajiag Normal Uiversity Zhajiag Guagdog, 54048 P.R. Chia
More informationMAT 271 Project: Partial Fractions for certain rational functions
MAT 7 Project: Partial Fractios for certai ratioal fuctios Prerequisite kowledge: partial fractios from MAT 7, a very good commad of factorig ad complex umbers from Precalculus. To complete this project,
More informationLINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity
LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 9 Multicolliearity Dr Shalabh Departmet of Mathematics ad Statistics Idia Istitute of Techology Kapur Multicolliearity diagostics A importat questio that
More informationTrue Nature of Potential Energy of a Hydrogen Atom
True Nature of Potetial Eergy of a Hydroge Atom Koshu Suto Key words: Bohr Radius, Potetial Eergy, Rest Mass Eergy, Classical Electro Radius PACS codes: 365Sq, 365-w, 33+p Abstract I cosiderig the potetial
More informationOn a Smarandache problem concerning the prime gaps
O a Smaradache problem cocerig the prime gaps Felice Russo Via A. Ifate 7 6705 Avezzao (Aq) Italy felice.russo@katamail.com Abstract I this paper, a problem posed i [] by Smaradache cocerig the prime gaps
More informationExact Solutions for a Class of Nonlinear Singular Two-Point Boundary Value Problems: The Decomposition Method
Exact Solutios for a Class of Noliear Sigular Two-Poit Boudary Value Problems: The Decompositio Method Abd Elhalim Ebaid Departmet of Mathematics, Faculty of Sciece, Tabuk Uiversity, P O Box 741, Tabuki
More informationNEW FAST CONVERGENT SEQUENCES OF EULER-MASCHERONI TYPE
UPB Sci Bull, Series A, Vol 79, Iss, 207 ISSN 22-7027 NEW FAST CONVERGENT SEQUENCES OF EULER-MASCHERONI TYPE Gabriel Bercu We itroduce two ew sequeces of Euler-Mascheroi type which have fast covergece
More informationENGI Series Page 6-01
ENGI 3425 6 Series Page 6-01 6. Series Cotets: 6.01 Sequeces; geeral term, limits, covergece 6.02 Series; summatio otatio, covergece, divergece test 6.03 Stadard Series; telescopig series, geometric series,
More informationCEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering
CEE 5 Autum 005 Ucertaity Cocepts for Geotechical Egieerig Basic Termiology Set A set is a collectio of (mutually exclusive) objects or evets. The sample space is the (collectively exhaustive) collectio
More informationSome properties of Boubaker polynomials and applications
Some properties of Boubaker polyomials ad applicatios Gradimir V. Milovaović ad Duša Joksimović Citatio: AIP Cof. Proc. 179, 1050 (2012); doi: 10.1063/1.756326 View olie: http://dx.doi.org/10.1063/1.756326
More information6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer.
6 Itegers Modulo I Example 2.3(e), we have defied the cogruece of two itegers a,b with respect to a modulus. Let us recall that a b (mod ) meas a b. We have proved that cogruece is a equivalece relatio
More informationON POINTWISE BINOMIAL APPROXIMATION
Iteratioal Joural of Pure ad Applied Mathematics Volume 71 No. 1 2011, 57-66 ON POINTWISE BINOMIAL APPROXIMATION BY w-functions K. Teerapabolar 1, P. Wogkasem 2 Departmet of Mathematics Faculty of Sciece
More informationOverview. p 2. Chapter 9. Pooled Estimate of. q = 1 p. Notation for Two Proportions. Inferences about Two Proportions. Assumptions
Chapter 9 Slide Ifereces from Two Samples 9- Overview 9- Ifereces about Two Proportios 9- Ifereces about Two Meas: Idepedet Samples 9-4 Ifereces about Matched Pairs 9-5 Comparig Variatio i Two Samples
More information17 Phonons and conduction electrons in solids (Hiroshi Matsuoka)
7 Phoos ad coductio electros i solids Hiroshi Matsuoa I this chapter we will discuss a miimal microscopic model for phoos i a solid ad a miimal microscopic model for coductio electros i a simple metal.
More informationStatistical Inference Based on Extremum Estimators
T. Rotheberg Fall, 2007 Statistical Iferece Based o Extremum Estimators Itroductio Suppose 0, the true value of a p-dimesioal parameter, is kow to lie i some subset S R p : Ofte we choose to estimate 0
More informationBasics of Probability Theory (for Theory of Computation courses)
Basics of Probability Theory (for Theory of Computatio courses) Oded Goldreich Departmet of Computer Sciece Weizma Istitute of Sciece Rehovot, Israel. oded.goldreich@weizma.ac.il November 24, 2008 Preface.
More informationSECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES
SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,
More informationMath 2784 (or 2794W) University of Connecticut
ORDERS OF GROWTH PAT SMITH Math 2784 (or 2794W) Uiversity of Coecticut Date: Mar. 2, 22. ORDERS OF GROWTH. Itroductio Gaiig a ituitive feel for the relative growth of fuctios is importat if you really
More informationThe Method of Least Squares. To understand least squares fitting of data.
The Method of Least Squares KEY WORDS Curve fittig, least square GOAL To uderstad least squares fittig of data To uderstad the least squares solutio of icosistet systems of liear equatios 1 Motivatio Curve
More informationOn Nonsingularity of Saddle Point Matrices. with Vectors of Ones
Iteratioal Joural of Algebra, Vol. 2, 2008, o. 4, 197-204 O Nosigularity of Saddle Poit Matrices with Vectors of Oes Tadeusz Ostrowski Istitute of Maagemet The State Vocatioal Uiversity -400 Gorzów, Polad
More informationLinear Regression Models
Liear Regressio Models Dr. Joh Mellor-Crummey Departmet of Computer Sciece Rice Uiversity johmc@cs.rice.edu COMP 528 Lecture 9 15 February 2005 Goals for Today Uderstad how to Use scatter diagrams to ispect
More informationOrthogonal Gaussian Filters for Signal Processing
Orthogoal Gaussia Filters for Sigal Processig Mark Mackezie ad Kiet Tieu Mechaical Egieerig Uiversity of Wollogog.S.W. Australia Abstract A Gaussia filter usig the Hermite orthoormal series of fuctios
More informationResponse Variable denoted by y it is the variable that is to be predicted measure of the outcome of an experiment also called the dependent variable
Statistics Chapter 4 Correlatio ad Regressio If we have two (or more) variables we are usually iterested i the relatioship betwee the variables. Associatio betwee Variables Two variables are associated
More informationChapter 10: Power Series
Chapter : Power Series 57 Chapter Overview: Power Series The reaso series are part of a Calculus course is that there are fuctios which caot be itegrated. All power series, though, ca be itegrated because
More information3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,
3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [
More informationA Simplified Binet Formula for k-generalized Fibonacci Numbers
A Simplified Biet Formula for k-geeralized Fiboacci Numbers Gregory P. B. Dresde Departmet of Mathematics Washigto ad Lee Uiversity Lexigto, VA 440 dresdeg@wlu.edu Zhaohui Du Shaghai, Chia zhao.hui.du@gmail.com
More informationAlternating Series. 1 n 0 2 n n THEOREM 9.14 Alternating Series Test Let a n > 0. The alternating series. 1 n a n.
0_0905.qxd //0 :7 PM Page SECTION 9.5 Alteratig Series Sectio 9.5 Alteratig Series Use the Alteratig Series Test to determie whether a ifiite series coverges. Use the Alteratig Series Remaider to approximate
More informationApplication to Random Graphs
A Applicatio to Radom Graphs Brachig processes have a umber of iterestig ad importat applicatios. We shall cosider oe of the most famous of them, the Erdős-Réyi radom graph theory. 1 Defiitio A.1. Let
More informationThe standard deviation of the mean
Physics 6C Fall 20 The stadard deviatio of the mea These otes provide some clarificatio o the distictio betwee the stadard deviatio ad the stadard deviatio of the mea.. The sample mea ad variace Cosider
More informationEstimation of Population Mean Using Co-Efficient of Variation and Median of an Auxiliary Variable
Iteratioal Joural of Probability ad Statistics 01, 1(4: 111-118 DOI: 10.593/j.ijps.010104.04 Estimatio of Populatio Mea Usig Co-Efficiet of Variatio ad Media of a Auxiliary Variable J. Subramai *, G. Kumarapadiya
More information(b) What is the probability that a particle reaches the upper boundary n before the lower boundary m?
MATH 529 The Boudary Problem The drukard s walk (or boudary problem) is oe of the most famous problems i the theory of radom walks. Oe versio of the problem is described as follows: Suppose a particle
More informationCHAPTER 5. Theory and Solution Using Matrix Techniques
A SERIES OF CLASS NOTES FOR 2005-2006 TO INTRODUCE LINEAR AND NONLINEAR PROBLEMS TO ENGINEERS, SCIENTISTS, AND APPLIED MATHEMATICIANS DE CLASS NOTES 3 A COLLECTION OF HANDOUTS ON SYSTEMS OF ORDINARY DIFFERENTIAL
More informationOFF-DIAGONAL MULTILINEAR INTERPOLATION BETWEEN ADJOINT OPERATORS
OFF-DIAGONAL MULTILINEAR INTERPOLATION BETWEEN ADJOINT OPERATORS LOUKAS GRAFAKOS AND RICHARD G. LYNCH 2 Abstract. We exted a theorem by Grafakos ad Tao [5] o multiliear iterpolatio betwee adjoit operators
More informationECE 901 Lecture 12: Complexity Regularization and the Squared Loss
ECE 90 Lecture : Complexity Regularizatio ad the Squared Loss R. Nowak 5/7/009 I the previous lectures we made use of the Cheroff/Hoeffdig bouds for our aalysis of classifier errors. Hoeffdig s iequality
More informationMath 113 Exam 3 Practice
Math Exam Practice Exam will cover.-.9. This sheet has three sectios. The first sectio will remid you about techiques ad formulas that you should kow. The secod gives a umber of practice questios for you
More informationAnalytic Theory of Probabilities
Aalytic Theory of Probabilities PS Laplace Book II Chapter II, 4 pp 94 03 4 A lottery beig composed of umbered tickets of which r exit at each drawig, oe requires the probability that after i drawigs all
More informationProperties and Hypothesis Testing
Chapter 3 Properties ad Hypothesis Testig 3.1 Types of data The regressio techiques developed i previous chapters ca be applied to three differet kids of data. 1. Cross-sectioal data. 2. Time series data.
More informationTR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT
TR/46 OCTOBER 974 THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION by A. TALBOT .. Itroductio. A problem i approximatio theory o which I have recetly worked [] required for its solutio a proof that the
More informationCommutativity in Permutation Groups
Commutativity i Permutatio Groups Richard Wito, PhD Abstract I the group Sym(S) of permutatios o a oempty set S, fixed poits ad trasiet poits are defied Prelimiary results o fixed ad trasiet poits are
More informationAxioms of Measure Theory
MATH 532 Axioms of Measure Theory Dr. Neal, WKU I. The Space Throughout the course, we shall let X deote a geeric o-empty set. I geeral, we shall ot assume that ay algebraic structure exists o X so that
More informationSimilarity between quantum mechanics and thermodynamics: Entropy, temperature, and Carnot cycle
Similarity betwee quatum mechaics ad thermodyamics: Etropy, temperature, ad Carot cycle Sumiyoshi Abe 1,,3 ad Shiji Okuyama 1 1 Departmet of Physical Egieerig, Mie Uiversity, Mie 514-8507, Japa Istitut
More informationOptimally Sparse SVMs
A. Proof of Lemma 3. We here prove a lower boud o the umber of support vectors to achieve geeralizatio bouds of the form which we cosider. Importatly, this result holds ot oly for liear classifiers, but
More informationThe Random Walk For Dummies
The Radom Walk For Dummies Richard A Mote Abstract We look at the priciples goverig the oe-dimesioal discrete radom walk First we review five basic cocepts of probability theory The we cosider the Beroulli
More informationChapter 6 Infinite Series
Chapter 6 Ifiite Series I the previous chapter we cosidered itegrals which were improper i the sese that the iterval of itegratio was ubouded. I this chapter we are goig to discuss a topic which is somewhat
More informationNumber of Spanning Trees of Circulant Graphs C 6n and their Applications
Joural of Mathematics ad Statistics 8 (): 4-3, 0 ISSN 549-3644 0 Sciece Publicatios Number of Spaig Trees of Circulat Graphs C ad their Applicatios Daoud, S.N. Departmet of Mathematics, Faculty of Sciece,
More informationRandić index, diameter and the average distance
Radić idex, diameter ad the average distace arxiv:0906.530v1 [math.co] 9 Ju 009 Xueliag Li, Yogtag Shi Ceter for Combiatorics ad LPMC-TJKLC Nakai Uiversity, Tiaji 300071, Chia lxl@akai.edu.c; shi@cfc.akai.edu.c
More informationComparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series
Applied Mathematical Scieces, Vol. 7, 03, o. 6, 3-337 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.03.3430 Compariso Study of Series Approimatio ad Covergece betwee Chebyshev ad Legedre Series
More informationHomework Set #3 - Solutions
EE 15 - Applicatios of Covex Optimizatio i Sigal Processig ad Commuicatios Dr. Adre Tkaceko JPL Third Term 11-1 Homework Set #3 - Solutios 1. a) Note that x is closer to x tha to x l i the Euclidea orm
More information1.3 Convergence Theorems of Fourier Series. k k k k. N N k 1. With this in mind, we state (without proof) the convergence of Fourier series.
.3 Covergece Theorems of Fourier Series I this sectio, we preset the covergece of Fourier series. A ifiite sum is, by defiitio, a limit of partial sums, that is, a cos( kx) b si( kx) lim a cos( kx) b si(
More informationProbability, Expectation Value and Uncertainty
Chapter 1 Probability, Expectatio Value ad Ucertaity We have see that the physically observable properties of a quatum system are represeted by Hermitea operators (also referred to as observables ) such
More informationIntroduction to Astrophysics Tutorial 2: Polytropic Models
Itroductio to Astrophysics Tutorial : Polytropic Models Iair Arcavi 1 Summary of the Equatios of Stellar Structure We have arrived at a set of dieretial equatios which ca be used to describe the structure
More informationTopic 9: Sampling Distributions of Estimators
Topic 9: Samplig Distributios of Estimators Course 003, 2018 Page 0 Samplig distributios of estimators Sice our estimators are statistics (particular fuctios of radom variables), their distributio ca be
More informationPrinciple Of Superposition
ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give
More information3.2 Properties of Division 3.3 Zeros of Polynomials 3.4 Complex and Rational Zeros of Polynomials
Math 60 www.timetodare.com 3. Properties of Divisio 3.3 Zeros of Polyomials 3.4 Complex ad Ratioal Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered
More information4 The Sperner property.
4 The Sperer property. I this sectio we cosider a surprisig applicatio of certai adjacecy matrices to some problems i extremal set theory. A importat role will also be played by fiite groups. I geeral,
More informationECE 8527: Introduction to Machine Learning and Pattern Recognition Midterm # 1. Vaishali Amin Fall, 2015
ECE 8527: Itroductio to Machie Learig ad Patter Recogitio Midterm # 1 Vaishali Ami Fall, 2015 tue39624@temple.edu Problem No. 1: Cosider a two-class discrete distributio problem: ω 1 :{[0,0], [2,0], [2,2],
More informationA Challenging Test For Convergence Accelerators: Summation Of A Series With A Special Sign Pattern
Applied Mathematics E-Notes, 6(006), 5-34 c ISSN 1607-510 Available free at mirror sites of http://www.math.thu.edu.tw/ ame/ A Challegig Test For Covergece Accelerators: Summatio Of A Series With A Special
More informationFor example suppose we divide the interval [0,2] into 5 equal subintervals of length
Math 1206 Calculus Sec 1: Estimatig with Fiite Sums Abbreviatios: wrt with respect to! for all! there exists! therefore Def defiitio Th m Theorem sol solutio! perpedicular iff or! if ad oly if pt poit
More informationDefinitions and Theorems. where x are the decision variables. c, b, and a are constant coefficients.
Defiitios ad Theorems Remember the scalar form of the liear programmig problem, Miimize, Subject to, f(x) = c i x i a 1i x i = b 1 a mi x i = b m x i 0 i = 1,2,, where x are the decisio variables. c, b,
More information