Strong Laws of Large Numbers for Fuzzy Set-Valued Random Variables in Gα Space

Size: px
Start display at page:

Download "Strong Laws of Large Numbers for Fuzzy Set-Valued Random Variables in Gα Space"

Transcription

1 Advaces Pure Matheatcs Publshed Ole August 26 ScRes Strog Laws of Large Nubers for uzzy Set-Valued Rado Varables G Space Lae She L Gua College of Appled Sceces Beg Uversty of Techology Beg Cha Receved 7 July 26; accepted 2 August 26; publshed 5 August 26 Copyrght 26 by authors ad Scetfc Research Publshg Ic Ths wor s lcesed uder the Creatve Coos Attrbuto Iteratoal Lcese (CC BY) Abstract I ths paper we shall preset the strog laws of large ubers for fuzzy set-valued rado varables the sese of d The results are based o the result of sgle-valued rado varables obtaed by Taylor [] ad set-valued rado varables obtaed by L Gua [2] Keywords Laws of Large Nubers uzzy Set-Valued Rado Varable ausdorff Metrc Itroducto Wth the developet of set-valued stochastc theory t has becoe a ew brach of probablty theory Ad lts theory s oe of the ost portat theores probablty ad statstcs May scholars have doe a lot of research ths aspect or exaple Artste ad Vtale [3] had proved the strog law of large ubers for depedet ad detcally dstrbuted rado varables by ebeddg theory a [4] had exteded t to separable Baach space Taylor ad Ioue had proved the strog law of large ubers for depedet rado varable the Baach space [5] May other scholars also had doe lots of wors the laws of large ubers for set-valued rado varables I [2] L proved the strog laws of large ubers for set-valued rado varables G space the sese of d etrc As we ow the fuzzy set s a exteso of the set Ad the cocept of fuzzy set-valued rado varables s a atural geeralzato of that of set-valued rado varables so t s ecessary to dscuss covergece theores of fuzzy set-valued rado sequece The lts of theores for fuzzy set-valued rado sequeces are also bee dscussed by ay researchers Colub et al [6] eg [7] ad Molchaov [8] proved the strog laws of large ubers for fuzzy set-valued rado varables; Pur ad Ralescu [9] L ad Ogura [] proved cover- ow to cte ths paper: She LM ad Gua L (26) Strog Laws of Large Nubers for uzzy Set-Valued Rado Varables G Space Advaces Pure Matheatcs

2 L M She L Gua gece theores for fuzzy set-valued artgales L ad Ogura [] proved the SLLN of [2] the sese of d by usg the sadwch ethod Gua ad L [3] proved the SLLN for weghted sus of fuzzy setvalued rado varables the sese of d whch used the sae ethod I ths paper what we cocered are the covergece theores of fuzzy set-valued sequece G space the sese of d The purpose of ths paper s to prove the strog laws of large ubers for fuzzy set-valued rado varables G space whch s both the exteso of the result [] for sgle-valued rado sequece ad also the exteso [2] for set-valued rado sequece Ths paper s orgazed as follows I Secto 2 we shall brefly troduce soe cocepts ad basc results of set-valued ad fuzzy set-valued rado varables I Secto 3 I shall prove the strog laws of large ubers for fuzzy set-valued rado varables G space whch s the sese of ausdorff etrc d 2 Prelares o Set-Valued Rado Varables Throughout ths paper we assue that ( Ω µ ) s a coplete probablty space ( ) Baach space K ( ) s the faly of all oepty closed subsets of ad b( ) ( ( ) ) of all o-epty bouded closed(copact) subsets of ad ( ) s a real separable K K s the faly K c s the faly of all o-epty copact covex subsets of Let A ad B be two oepty subsets of ad let λ the set of all real ubers We defe addto ad scalar ultplcato by The ausdorff etrc o K ( ) s defed by { : } A+ B= a+ b a Ab B { λ : } λa= a a A ( ) = ax { supf supf b B a A } d A B a b a b a A for AB K ( ) or a A K ( ) let A = d ({ } A K ) The etrc space ( K b( ) d ) s coplete ad K bc ( ) s a closed subset of ( b( ) d ) b B K (cf [4] Theores 2 ad 3) or ore geeral hyperspaces ore topologcal propertes of hyperspaces readers ay refer to the boos [5] ad [4] A K defe the support fucto by or each s x * A = sup x * a x * * * where s the dual space of * * * Let S deote the ut sphere of C ( S ) the all cotuous fuctos of as v = sup C x S The followg s the equvalet defto of ausdorff etrc AB K bc or each a A * * * * { } d A B = sup s x A s x A : x S A set-valued appg : fucto) f for each ope subset O of ( O) { ω : ( ω) O } or each set-valued rado varable the expectato of deoted by [ ] * S ad the or s defed Ω K s called a set-valued rado varable (or a rado set or a ult- = Ω E s defed by [ ] = { µ } E fd : f S Ω where f d µ s the usual Bocher tegral L [ Ω ] the faly of tegrable -valued rado varables Ω S = f L Ω; : f ω ω ae µ { } ad [ ] 584

3 L M She L Gua Let ( ) deote the faly of all fuctos v : [ ] whch satsfy the followg codtos: ) The level set v = { x : v( x) = } 2) Each v s upper secotuous e for each ( ] the level set v = { x : v( x) } closed subset of 3) The support set v = cl { x + : v ( x) > } s copact A fucto v ( ) s called covex f t satsfes v( λx+ ( λ) y) { v( x) v( y) } s a for ay xy λ ( ] Let c ( ) be the subset of all covex fuzzy sets ( ) It s ow that v s covex the above sese f ad oly f for ay ( ] subset of (cf Theore 32 of [6]) or ay v ( ) the closed covex hull cov c cov = for all ( ] defed by the relato or ay two fuzzy sets 2 cov ν ν defe ( ] { } ν + ν 2 x = sup : x ν 2 + ν for ay x Slarly for a fuzzy set ν ad a real uber λ defe for ay x The followg two etrcs ( ) ad [8] or [4]): for v v 2 ( ) Deote x The space ( ) ( λν )( x) = { ( ] x λν } sup : the level set v s a covex of v s whch are extesos of the ausdorff etrc d are ofte used (cf [7] ( ) d v v = sup d v v 2 2 ( ] d v v = d v v d 2 2 v = : d vi = sup > v where I K s the fuzzy set tag value oe at ad zero for all ( d ) s a coplete etrc space (cf [8] or [4]: Theore 56) but ot separable (cf [7] or [4]: Rear 57) It s well ow that v v d every Cauchy sequece { } ( ) = for every ( ] < Due to the copleteess of v : has a lt v ( ) A fuzzy set-valued rado varable (or a fuzzy rado set or a fuzzy rado varable lterature) s a appg : Ω ( ) such that ( ω) = { x : ( ω)( x) } s a set-valued rado varable for every ( ] (cf [8] or [4]) The expectato of ay fuzzy set-valued rado varable deoted by E[ ] s a eleet ( ) such that for every ( ] ( E[ ] ) E[ ] = where the expectato of rght had s Aua tegral ro the exstece theore (cf [9]) we ca get a equvalet defto: for ay x Note that E[ ] s always covex whe ( µ ) 3 Ma Results = { [ ] [ ]} E x sup : x E Ω s oatoc I ths secto we wll gve the lt theores for fuzzy set-valued rado varables G space I wll frstly 585

4 L M She L Gua troduce the defto of G space The followg Defto 3 ad Lea 32 are fro Taylor s boo [8] whch wll be used later Defto 3 A Baach space s sad to satsfy the codto G for soe ( ] If there exsts a appg G : such that ) G( x) 2) = x ; G x x x + = ; 3) G( x) G( y) = Ax y for all xy ad soe postve costat A Note that lbert spaces are G wth costat A = ad detty appg G Lea 32 Let be a Baach space whch satsfes the codto of G { V V2 V} be depedet E V < + for each = 2 The rado eleets such that EV [ ] = ad = E V V A E V where A s the postve costat 3) of defto 3 I order to obta the a results we frstly eed to prove Lea 35 The followg lea are fro [4] (cf p89 Lea 34) whch wll be used to prove Lea 35 C : N K If Lea 33 Let { } be a sequece for soe C K ( ) c the Lea 34 (cf [3]) or ay ν ( ) l d coc C = = l d C C = = there exsts a fte ( ) d ν ν + ε for all = M t t Now we prove that the result of Lea 33 s also true for fuzzy sets : If Lea 35 Let { } for soe ν ( ) c ν be a sequece the Proof By (3) we ca have = t < t < < t M = such that l d coν ν = (3) = l d ν ν = = ad l d coν ν = = for ( ] The by Lea 33 for ( ] l d coν+ ν+ = = we have 586

5 L M She L Gua ad l d ν ν = = l d ν+ ν+ = = By Lea 34 tae a ε > there exsts a fte = < < < M = such that The for < < Cosequetly d ( ) ν ν ε for all M + d ν ν d ν ν d ν ν + = + = = d + d + d ν ν 2 ν ν ν ν = = sup ν ν ax ν ν + ax ν ν + 2 ε d d ( ] d M M + + = = = Sce the frst two ters o the rght had coverge to probablty oe we have but ε s arbtrary ad the result follows l sup sup d ν ν 2 ε ( ] = Theore 36 Let be a Baach space whch satsfes the codto of G let { } : be depe- for ay If det fuzzy set-valued rado varables where = for t ad t t of d Proof Defe Note that such that E = I = ( ) E < + t = t for t the U = I W = I { } { > } = + for each ad both { W : } ad { : } W U fuzzy set-valued rado varables Whe > we have for ay E W E W E coverges wth probablty the sese = W U are depedet sequece of = ad = = = = = The Ad fro E < we ow that = E W : = s a Cauchy sequece So we have 587

6 L M She L Gua E W coverges as = Sce covergece the ea pled covergece probablty Ito ad Nsos result [9] for depedet rado eleets (cf Secto 45) provdes that = So for ay > by tragle equalty we have It eas we have W coverges probablty d W W = d W W + W = = = = = + d W W + d I W = = = + = d I W = + = W ae as = + W : s a Cauchy sequece the sese of = W coverges alost everywhere the sese of = Next we shall prove that d U coverges the sese of = ( d ) d By the copleteess of ( ) d rstly we assue that { } fuzzy set-valued rado varables The by the equvalet defto of ausdorff etrc we have or ay fxed there exsts a sequece E U = E sup U = ( ] = K = E sup d U { } ( ] = = E sup sup s x U ( ] x S = x S such that l s x U = sup s x U = x S = U are all covex That eas there exst a sequece x S such that E U = E sup l s x U ( ] = = The by Cr equalty doated covergece theore ad Lea 32 we have 588

7 L M She L Gua E U = E sup l s x U ( ] = = for each ad E sup l s( x U ) ( ] = E l sup s( x U ) ( ] = l E sup s( x U ) Es( x U ) + Es( x U ) ( ] = = l E l s( x U ) Es( x ) ( ) U + Es x U = = l l E s( x U ) Es( x ) ( ) U + Es x U = l l E s x U E s x U + E s x U = = ( ) ( ) ( ) l l 2 E s( x U ) Es( x ) ( ) U + Es x U = = l l 2 AE s( x U ) E s( x ) ( ) U Es x U + = = l l 2 2 A E s( x U ) 2 A E s( x ) ( ) U Es x W + + = = = l l 2 2 A E s x U 2 A E s x U E + + = = = ( ) ( ) s( x W ) 2+ = l l 2 2 A E s( x U ) E s( x ) W + = = 2+ l 2 2 AE sup s( x U ) E sup s( x W ) + * * * * = x S = x S = l 2 2 A E U + E W K K = = = 2 2 A E U + E W = = = = A E ( ) E ( ) 589

8 L M She L Gua The we ow E = U Thus by the slar way as above to prove ca prove that wth probablty the sese of So we ca prove that wth probablty the sese of cou coverges wth proba- = blty the sese of d s a Cauchy sequece ece { E U = } s a Cauchy sequece W coverges wth probablty the sese of = = U coverges d I fact for each d U U = d U U + U = = = = = + d If { } = U = + ae as coverges U are ot covex we ca prove as above ad by the Lea 35 we ca prove that d We also U coverges wth proba= blty the sese of d The the result was proved ro Theore 36 we ca easly obta the followg corollary Corollary 37 Let be a separable Baach space whch s G for soe < Let { : } be a sequece of depedet fuzzy set-valued rado varables ( ) such that E = I for each If + + ( t) t : = 2 are cotuous ad such that ad are o-decreasg the for each t t + the covergece of ples that E ( ) ( ) = coverges wth probablty oe the sese of d Proof Let U = I ad W = I > If > by the o-decreasg property of = { } { } ( t) t we have ( ) ( ) 59

9 L M She L Gua That s ( ) (4) If by the o-decreasg property of t ( t) we have That s ( ) ( ) + (42) The as the slar proof of Theore 36 we ca prove both oe the sese of d ad the result was obtaed U ad = W coverges wth probablty = Acowledgeets We tha the Edtor ad the referee for ther coets Research of L Gua s fuded by the NSC ( ) Refereces [] Taylor RL (978) Lecture Notes Matheatcs Sprger-Verlag 672 [2] L G (25) A Strog Law of Large Nubers for Set-Valued Rado Varables G Space Joural of Appled Matheatcs ad Physcs [3] Artste Z ad Vtale RA (975) A Strog Law of Large Nubers for Rado Copact Sets Aals of Probablty [4] a (984) Strog Laws of Large Nubers for Multvalued Rado Varables Multfuctos ad Itegrads I: Salett G Ed Lecture Notes Matheatcs Vol 9 Sprger Berl 6-72 [5] Taylor RL ad Ioue (985) A Strog Law of Large Nubers for Rado Sets Baach Spaces Bullet of the Isttute of Matheatcs Acadea Sca [6] Colub A López-Díaz M Doguez-Mechero JS ad Gl MA (999) A Geeralzed Strog Law of Large Nubers Probablty Theory ad Related elds [7] eg Y (24) Strog Law of Large Nubers for Statoary Sequeces of Rado Upper Secotuous uctos Stochastc Aalyss ad Applcatos [8] Molchaov I (999) O Strog Laws of Large Nubers for Rado Upper Secotuous uctos Joural of Matheatcal Aalyss ad Applcatos [9] Pur ML ad Ralescu DA (99) Covergece Theore for uzzy Martgales Joural of Matheatcal Aalyss ad Applcatos [] L S ad Ogura Y (23) A Covergece Theore of uzzy Valued Martgale the Exteded ausdorff Metrc uzzy Sets ad Systes [] L S ad Ogura Y (23) Strog Laws of Nubers for Idepedet uzzy Set-Valued Rado Varables uzzy Sets ad Systes [2] Ioue (99) A Strog Law of Large Nubers for uzzy Rado Sets uzzy Sets ad Systes [3] Gua L ad L S (24) Laws of Large Nubers for Weghted Sus of uzzy Set-Valued Rado Varables Iteratoal Joural of Ucertaty uzzess ad Kowledge-Based Systes

10 L M She L Gua [4] L S Ogura Y ad Kreovch V (22) Lt Theores ad Applcatos of Set-Valued ad uzzy Set-Valued Rado Varables Kluwer Acadec Publshers Dordrecht [5] Beer G (993) Topologes o Closed ad Closed Covex Sets Matheatcs ad Its Applcatos Kluwer Acadec Publshers Dordrecht ollad [6] Che Y (984) uzzy Systes ad Matheatcs uazhog Isttute Press of Scece ad Techology Wuha (I Chese) [7] Kleet EP Pur LM ad Ralescu DA (986) Lt Theores for uzzy Rado Varables Proceedgs of the Royal Socety of Lodo A [8] Pur ML ad Ralescu DA (986) uzzy Rado Varables Joural of Matheatcal Aalyss ad Applcatos [9] L S ad Ogura Y (996) uzzy Rado Varables Codtoal Expectatos ad uzzy Martgales Joural of uzzy Matheatcs Subt or recoed ext auscrpt to SCIRP ad we wll provde best servce for you: Acceptg pre-subsso qures through Eal aceboo LedI Twtter etc A wde selecto of ourals (clusve of 9 subects ore tha 2 ourals) Provdg 24-hour hgh-qualty servce User-fredly ole subsso syste ar ad swft peer-revew syste Effcet typesettg ad proofreadg procedure Dsplay of the result of dowloads ad vsts as well as the uber of cted artcles Maxu dsseato of your research wor Subt your auscrpt at: 592

A Remark on the Uniform Convergence of Some Sequences of Functions

A Remark on the Uniform Convergence of Some Sequences of Functions Advaces Pure Mathematcs 05 5 57-533 Publshed Ole July 05 ScRes. http://www.scrp.org/joural/apm http://dx.do.org/0.436/apm.05.59048 A Remark o the Uform Covergece of Some Sequeces of Fuctos Guy Degla Isttut

More information

Hájek-Rényi Type Inequalities and Strong Law of Large Numbers for NOD Sequences

Hájek-Rényi Type Inequalities and Strong Law of Large Numbers for NOD Sequences Appl Math If Sc 7, No 6, 59-53 03 59 Appled Matheatcs & Iforato Sceces A Iteratoal Joural http://dxdoorg/0785/as/070647 Háje-Réy Type Iequaltes ad Strog Law of Large Nuers for NOD Sequeces Ma Sogl Departet

More information

A Family of Non-Self Maps Satisfying i -Contractive Condition and Having Unique Common Fixed Point in Metrically Convex Spaces *

A Family of Non-Self Maps Satisfying i -Contractive Condition and Having Unique Common Fixed Point in Metrically Convex Spaces * Advaces Pure Matheatcs 0 80-84 htt://dxdoorg/0436/a04036 Publshed Ole July 0 (htt://wwwscrporg/oural/a) A Faly of No-Self Mas Satsfyg -Cotractve Codto ad Havg Uque Coo Fxed Pot Metrcally Covex Saces *

More information

Research Article A New Iterative Method for Common Fixed Points of a Finite Family of Nonexpansive Mappings

Research Article A New Iterative Method for Common Fixed Points of a Finite Family of Nonexpansive Mappings Hdaw Publshg Corporato Iteratoal Joural of Mathematcs ad Mathematcal Sceces Volume 009, Artcle ID 391839, 9 pages do:10.1155/009/391839 Research Artcle A New Iteratve Method for Commo Fxed Pots of a Fte

More information

Complete Convergence and Some Maximal Inequalities for Weighted Sums of Random Variables

Complete Convergence and Some Maximal Inequalities for Weighted Sums of Random Variables Joural of Sceces, Islamc Republc of Ira 8(4): -6 (007) Uversty of Tehra, ISSN 06-04 http://sceces.ut.ac.r Complete Covergece ad Some Maxmal Iequaltes for Weghted Sums of Radom Varables M. Am,,* H.R. Nl

More information

Global Optimization for Solving Linear Non-Quadratic Optimal Control Problems

Global Optimization for Solving Linear Non-Quadratic Optimal Control Problems Joural of Appled Matheatcs ad Physcs 06 4 859-869 http://wwwscrporg/joural/jap ISSN Ole: 37-4379 ISSN Prt: 37-435 Global Optzato for Solvg Lear No-Quadratc Optal Cotrol Probles Jghao Zhu Departet of Appled

More information

A New Method for Solving Fuzzy Linear. Programming by Solving Linear Programming

A New Method for Solving Fuzzy Linear. Programming by Solving Linear Programming ppled Matheatcal Sceces Vol 008 o 50 7-80 New Method for Solvg Fuzzy Lear Prograg by Solvg Lear Prograg S H Nasser a Departet of Matheatcs Faculty of Basc Sceces Mazadara Uversty Babolsar Ira b The Research

More information

Journal Of Inequalities And Applications, 2008, v. 2008, p

Journal Of Inequalities And Applications, 2008, v. 2008, p Ttle O verse Hlbert-tye equaltes Authors Chagja, Z; Cheug, WS Ctato Joural Of Iequaltes Ad Alcatos, 2008, v. 2008,. 693248 Issued Date 2008 URL htt://hdl.hadle.et/0722/56208 Rghts Ths work s lcesed uder

More information

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi-Objective Programming

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi-Objective Programming Aerca Joural of Operatos Research, 4, 4, 33-339 Publshed Ole Noveber 4 ScRes http://wwwscrporg/oural/aor http://ddoorg/436/aor4463 A Pealty Fucto Algorth wth Obectve Paraeters ad Costrat Pealty Paraeter

More information

A Characterization of Jacobson Radical in Γ-Banach Algebras

A Characterization of Jacobson Radical in Γ-Banach Algebras Advaces Pure Matheatcs 43-48 http://dxdoorg/436/ap66 Publshed Ole Noveber (http://wwwscrporg/joural/ap) A Characterzato of Jacobso Radcal Γ-Baach Algebras Nlash Goswa Departet of Matheatcs Gauhat Uversty

More information

SUBCLASS OF HARMONIC UNIVALENT FUNCTIONS ASSOCIATED WITH SALAGEAN DERIVATIVE. Sayali S. Joshi

SUBCLASS OF HARMONIC UNIVALENT FUNCTIONS ASSOCIATED WITH SALAGEAN DERIVATIVE. Sayali S. Joshi Faculty of Sceces ad Matheatcs, Uversty of Nš, Serba Avalable at: http://wwwpfacyu/float Float 3:3 (009), 303 309 DOI:098/FIL0903303J SUBCLASS OF ARMONIC UNIVALENT FUNCTIONS ASSOCIATED WIT SALAGEAN DERIVATIVE

More information

Research Article Some Strong Limit Theorems for Weighted Product Sums of ρ-mixing Sequences of Random Variables

Research Article Some Strong Limit Theorems for Weighted Product Sums of ρ-mixing Sequences of Random Variables Hdaw Publshg Corporato Joural of Iequaltes ad Applcatos Volume 2009, Artcle ID 174768, 10 pages do:10.1155/2009/174768 Research Artcle Some Strog Lmt Theorems for Weghted Product Sums of ρ-mxg Sequeces

More information

International Journal of Mathematical Archive-5(8), 2014, Available online through ISSN

International Journal of Mathematical Archive-5(8), 2014, Available online through   ISSN Iteratoal Joural of Mathematcal Archve-5(8) 204 25-29 Avalable ole through www.jma.fo ISSN 2229 5046 COMMON FIXED POINT OF GENERALIZED CONTRACTION MAPPING IN FUZZY METRIC SPACES Hamd Mottagh Golsha* ad

More information

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

More information

Unique Common Fixed Point of Sequences of Mappings in G-Metric Space M. Akram *, Nosheen

Unique Common Fixed Point of Sequences of Mappings in G-Metric Space M. Akram *, Nosheen Vol No : Joural of Facult of Egeerg & echolog JFE Pages 9- Uque Coo Fed Pot of Sequeces of Mags -Metrc Sace M. Ara * Noshee * Deartet of Matheatcs C Uverst Lahore Pasta. Eal: ara7@ahoo.co Deartet of Matheatcs

More information

Complete Convergence for Weighted Sums of Arrays of Rowwise Asymptotically Almost Negative Associated Random Variables

Complete Convergence for Weighted Sums of Arrays of Rowwise Asymptotically Almost Negative Associated Random Variables A^VÇÚO 1 32 ò 1 5 Ï 2016 c 10 Chese Joural of Appled Probablty ad Statstcs Oct., 2016, Vol. 32, No. 5, pp. 489-498 do: 10.3969/j.ss.1001-4268.2016.05.005 Complete Covergece for Weghted Sums of Arrays of

More information

OPTIMALITY CONDITIONS FOR LOCALLY LIPSCHITZ GENERALIZED B-VEX SEMI-INFINITE PROGRAMMING

OPTIMALITY CONDITIONS FOR LOCALLY LIPSCHITZ GENERALIZED B-VEX SEMI-INFINITE PROGRAMMING Mrcea cel Batra Naval Acadey Scetfc Bullet, Volue XIX 6 Issue he joural s dexed : PROQUES / DOAJ / Crossref / EBSCOhost / INDEX COPERNICUS / DRJI / OAJI / JOURNAL INDEX / IOR / SCIENCE LIBRARY INDEX /

More information

X ε ) = 0, or equivalently, lim

X ε ) = 0, or equivalently, lim Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece

More information

Strong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity

Strong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity BULLETIN of the MALAYSIAN MATHEMATICAL SCIENCES SOCIETY Bull. Malays. Math. Sc. Soc. () 7 (004), 5 35 Strog Covergece of Weghted Averaged Appromats of Asymptotcally Noepasve Mappgs Baach Spaces wthout

More information

Almost Sure Convergence of Pair-wise NQD Random Sequence

Almost Sure Convergence of Pair-wise NQD Random Sequence www.ccseet.org/mas Moder Appled Scece Vol. 4 o. ; December 00 Almost Sure Covergece of Par-wse QD Radom Sequece Yachu Wu College of Scece Gul Uversty of Techology Gul 54004 Cha Tel: 86-37-377-6466 E-mal:

More information

A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions

A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions Appled Matheatcs, 1, 4, 8-88 http://d.do.org/1.4/a.1.448 Publshed Ole Aprl 1 (http://www.scrp.org/joural/a) A Covetoal Approach for the Soluto of the Ffth Order Boudary Value Probles Usg Sth Degree Sple

More information

Extend the Borel-Cantelli Lemma to Sequences of. Non-Independent Random Variables

Extend the Borel-Cantelli Lemma to Sequences of. Non-Independent Random Variables ppled Mathematcal Sceces, Vol 4, 00, o 3, 637-64 xted the Borel-Catell Lemma to Sequeces of No-Idepedet Radom Varables olah Der Departmet of Statstc, Scece ad Research Campus zad Uversty of Tehra-Ira der53@gmalcom

More information

STRONG CONSISTENCY FOR SIMPLE LINEAR EV MODEL WITH v/ -MIXING

STRONG CONSISTENCY FOR SIMPLE LINEAR EV MODEL WITH v/ -MIXING Joural of tatstcs: Advaces Theory ad Alcatos Volume 5, Number, 6, Pages 3- Avalable at htt://scetfcadvaces.co. DOI: htt://d.do.org/.864/jsata_7678 TRONG CONITENCY FOR IMPLE LINEAR EV MODEL WITH v/ -MIXING

More information

Non-uniform Turán-type problems

Non-uniform Turán-type problems Joural of Combatoral Theory, Seres A 111 2005 106 110 wwwelsevercomlocatecta No-uform Turá-type problems DhruvMubay 1, Y Zhao 2 Departmet of Mathematcs, Statstcs, ad Computer Scece, Uversty of Illos at

More information

MULTIOBJECTIVE NONLINEAR FRACTIONAL PROGRAMMING PROBLEMS INVOLVING GENERALIZED d - TYPE-I n -SET FUNCTIONS

MULTIOBJECTIVE NONLINEAR FRACTIONAL PROGRAMMING PROBLEMS INVOLVING GENERALIZED d - TYPE-I n -SET FUNCTIONS THE PUBLIHING HOUE PROCEEDING OF THE ROMANIAN ACADEMY, eres A OF THE ROMANIAN ACADEMY Volue 8, Nuber /27,.- MULTIOBJECTIVE NONLINEAR FRACTIONAL PROGRAMMING PROBLEM INVOLVING GENERALIZED d - TYPE-I -ET

More information

Relations to Other Statistical Methods Statistical Data Analysis with Positive Definite Kernels

Relations to Other Statistical Methods Statistical Data Analysis with Positive Definite Kernels Relatos to Other Statstcal Methods Statstcal Data Aalyss wth Postve Defte Kerels Kej Fukuzu Isttute of Statstcal Matheatcs, ROIS Departet of Statstcal Scece, Graduate Uversty for Advaced Studes October

More information

PROJECTION PROBLEM FOR REGULAR POLYGONS

PROJECTION PROBLEM FOR REGULAR POLYGONS Joural of Mathematcal Sceces: Advaces ad Applcatos Volume, Number, 008, Pages 95-50 PROJECTION PROBLEM FOR REGULAR POLYGONS College of Scece Bejg Forestry Uversty Bejg 0008 P. R. Cha e-mal: sl@bjfu.edu.c

More information

. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1)

. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1) Chapter 7 Fuctos o Bouded Varato. Subject: Real Aalyss Level: M.Sc. Source: Syed Gul Shah (Charma, Departmet o Mathematcs, US Sargodha Collected & Composed by: Atq ur Rehma (atq@mathcty.org, http://www.mathcty.org

More information

Sebastián Martín Ruiz. Applications of Smarandache Function, and Prime and Coprime Functions

Sebastián Martín Ruiz. Applications of Smarandache Function, and Prime and Coprime Functions Sebastá Martí Ruz Alcatos of Saradache Fucto ad Pre ad Core Fuctos 0 C L f L otherwse are core ubers Aerca Research Press Rehoboth 00 Sebastá Martí Ruz Avda. De Regla 43 Choa 550 Cadz Sa Sarada@telele.es

More information

Some Different Perspectives on Linear Least Squares

Some Different Perspectives on Linear Least Squares Soe Dfferet Perspectves o Lear Least Squares A stadard proble statstcs s to easure a respose or depedet varable, y, at fed values of oe or ore depedet varables. Soetes there ests a deterstc odel y f (,,

More information

The Mathematical Appendix

The Mathematical Appendix The Mathematcal Appedx Defto A: If ( Λ, Ω, where ( λ λ λ whch the probablty dstrbutos,,..., Defto A. uppose that ( Λ,,..., s a expermet type, the σ-algebra o λ λ λ are defed s deoted by ( (,,...,, σ Ω.

More information

Q-analogue of a Linear Transformation Preserving Log-concavity

Q-analogue of a Linear Transformation Preserving Log-concavity Iteratoal Joural of Algebra, Vol. 1, 2007, o. 2, 87-94 Q-aalogue of a Lear Trasformato Preservg Log-cocavty Daozhog Luo Departmet of Mathematcs, Huaqao Uversty Quazhou, Fua 362021, P. R. Cha ldzblue@163.com

More information

A New Method for Decision Making Based on Soft Matrix Theory

A New Method for Decision Making Based on Soft Matrix Theory Joural of Scetfc esearch & eports 3(5): 0-7, 04; rtcle o. JS.04.5.00 SCIENCEDOMIN teratoal www.scecedoma.org New Method for Decso Mag Based o Soft Matrx Theory Zhmg Zhag * College of Mathematcs ad Computer

More information

THE PROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION

THE PROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION Joural of Scece ad Arts Year 12, No. 3(2), pp. 297-32, 212 ORIGINAL AER THE ROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION DOREL MIHET 1, CLAUDIA ZAHARIA 1 Mauscrpt receved: 3.6.212; Accepted

More information

Entropy ISSN by MDPI

Entropy ISSN by MDPI Etropy 2003, 5, 233-238 Etropy ISSN 1099-4300 2003 by MDPI www.mdp.org/etropy O the Measure Etropy of Addtve Cellular Automata Hasa Aı Arts ad Sceces Faculty, Departmet of Mathematcs, Harra Uversty; 63100,

More information

On Convergence a Variation of the Converse of Fabry Gap Theorem

On Convergence a Variation of the Converse of Fabry Gap Theorem Scece Joural of Appled Matheatcs ad Statstcs 05; 3(): 58-6 Pulshed ole Aprl 05 (http://www.scecepulshggroup.co//sas) do: 0.648/.sas.05030.5 ISSN: 376-949 (Prt); ISSN: 376-953 (Ole) O Covergece a Varato

More information

Generalized Convex Functions on Fractal Sets and Two Related Inequalities

Generalized Convex Functions on Fractal Sets and Two Related Inequalities Geeralzed Covex Fuctos o Fractal Sets ad Two Related Iequaltes Huxa Mo, X Su ad Dogya Yu 3,,3School of Scece, Bejg Uversty of Posts ad Telecommucatos, Bejg,00876, Cha, Correspodece should be addressed

More information

Research Article Multidimensional Hilbert-Type Inequalities with a Homogeneous Kernel

Research Article Multidimensional Hilbert-Type Inequalities with a Homogeneous Kernel Hdaw Publshg Corporato Joural of Iequaltes ad Applcatos Volume 29, Artcle ID 3958, 2 pages do:.55/29/3958 Research Artcle Multdmesoal Hlbert-Type Iequaltes wth a Homogeeous Kerel Predrag Vuovć Faculty

More information

ON WEIGHTED INTEGRAL AND DISCRETE OPIAL TYPE INEQUALITIES

ON WEIGHTED INTEGRAL AND DISCRETE OPIAL TYPE INEQUALITIES M atheatcal I equaltes & A pplcatos Volue 19, Nuber 4 16, 195 137 do:1.7153/a-19-95 ON WEIGHTED INTEGRAL AND DISCRETE OPIAL TYPE INEQUALITIES MAJA ANDRIĆ, JOSIP PEČARIĆ AND IVAN PERIĆ Coucated by C. P.

More information

Research Article Gauss-Lobatto Formulae and Extremal Problems

Research Article Gauss-Lobatto Formulae and Extremal Problems Hdaw Publshg Corporato Joural of Iequaltes ad Applcatos Volume 2008 Artcle ID 624989 0 pages do:055/2008/624989 Research Artcle Gauss-Lobatto Formulae ad Extremal Problems wth Polyomals Aa Mara Acu ad

More information

Lebesgue Measure of Generalized Cantor Set

Lebesgue Measure of Generalized Cantor Set Aals of Pure ad Appled Mathematcs Vol., No.,, -8 ISSN: -8X P), -888ole) Publshed o 8 May www.researchmathsc.org Aals of Lebesgue Measure of Geeralzed ator Set Md. Jahurul Islam ad Md. Shahdul Islam Departmet

More information

ON THE LOGARITHMIC INTEGRAL

ON THE LOGARITHMIC INTEGRAL Hacettepe Joural of Mathematcs ad Statstcs Volume 39(3) (21), 393 41 ON THE LOGARITHMIC INTEGRAL Bra Fsher ad Bljaa Jolevska-Tueska Receved 29:9 :29 : Accepted 2 :3 :21 Abstract The logarthmc tegral l(x)

More information

Standard Deviation for PDG Mass Data

Standard Deviation for PDG Mass Data 4 Dec 06 Stadard Devato for PDG Mass Data M. J. Gerusa Retred, 47 Clfde Road, Worghall, HP8 9JR, UK. gerusa@aol.co, phoe: +(44) 844 339754 Abstract Ths paper aalyses the data for the asses of eleetary

More information

Exchangeable Sequences, Laws of Large Numbers, and the Mortgage Crisis.

Exchangeable Sequences, Laws of Large Numbers, and the Mortgage Crisis. Exchageable Sequeces, Laws of Large Numbers, ad the Mortgage Crss. Myug Joo Sog Advsor: Prof. Ja Madel May 2009 Itroducto The law of large umbers for..d. sequece gves covergece of sample meas to a costat,.e.,

More information

Large and Moderate Deviation Principles for Kernel Distribution Estimator

Large and Moderate Deviation Principles for Kernel Distribution Estimator Iteratoal Mathematcal Forum, Vol. 9, 2014, o. 18, 871-890 HIKARI Ltd, www.m-hkar.com http://dx.do.org/10.12988/mf.2014.4488 Large ad Moderate Devato Prcples for Kerel Dstrbuto Estmator Yousr Slaou Uversté

More information

Aitken delta-squared generalized Juncgk-type iterative procedure

Aitken delta-squared generalized Juncgk-type iterative procedure Atke delta-squared geeralzed Jucgk-type teratve procedure M. De la Se Isttute of Research ad Developmet of Processes. Uversty of Basque Coutry Campus of Leoa (Bzkaa) PO Box. 644- Blbao, 488- Blbao. SPAIN

More information

THE TRUNCATED RANDIĆ-TYPE INDICES

THE TRUNCATED RANDIĆ-TYPE INDICES Kragujeac J Sc 3 (00 47-5 UDC 547:54 THE TUNCATED ANDIĆ-TYPE INDICES odjtaba horba, a ohaad Al Hossezadeh, b Ia uta c a Departet of atheatcs, Faculty of Scece, Shahd ajae Teacher Trag Uersty, Tehra, 785-3,

More information

A Note on the Almost Sure Central Limit Theorem in the Joint Version for the Maxima and Partial Sums of Certain Stationary Gaussian Sequences *

A Note on the Almost Sure Central Limit Theorem in the Joint Version for the Maxima and Partial Sums of Certain Stationary Gaussian Sequences * Appe Matheatcs 0 5 598-608 Pubshe Oe Jue 0 ScRes http://wwwscrporg/joura/a http://xoorg/06/a0505 A Note o the Aost Sure Cetra Lt Theore the Jot Verso for the Maxa a Parta Sus of Certa Statoary Gaussa Sequeces

More information

= lim. (x 1 x 2... x n ) 1 n. = log. x i. = M, n

= lim. (x 1 x 2... x n ) 1 n. = log. x i. = M, n .. Soluto of Problem. M s obvously cotuous o ], [ ad ], [. Observe that M x,..., x ) M x,..., x ) )..) We ext show that M s odecreasg o ], [. Of course.) mles that M s odecreasg o ], [ as well. To show

More information

X X X E[ ] E X E X. is the ()m n where the ( i,)th. j element is the mean of the ( i,)th., then

X X X E[ ] E X E X. is the ()m n where the ( i,)th. j element is the mean of the ( i,)th., then Secto 5 Vectors of Radom Varables Whe workg wth several radom varables,,..., to arrage them vector form x, t s ofte coveet We ca the make use of matrx algebra to help us orgaze ad mapulate large umbers

More information

Further Results on Pair Sum Labeling of Trees

Further Results on Pair Sum Labeling of Trees Appled Mathematcs 0 70-7 do:046/am0077 Publshed Ole October 0 (http://wwwscrporg/joural/am) Further Results o Par Sum Labelg of Trees Abstract Raja Poraj Jeyaraj Vjaya Xaver Parthpa Departmet of Mathematcs

More information

Part 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971))

Part 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971)) art 4b Asymptotc Results for MRR usg RESS Recall that the RESS statstc s a specal type of cross valdato procedure (see Alle (97)) partcular to the regresso problem ad volves fdg Y $,, the estmate at the

More information

Asymptotic Formulas Composite Numbers II

Asymptotic Formulas Composite Numbers II Iteratoal Matematcal Forum, Vol. 8, 203, o. 34, 65-662 HIKARI Ltd, www.m-kar.com ttp://d.do.org/0.2988/mf.203.3854 Asymptotc Formulas Composte Numbers II Rafael Jakmczuk Dvsó Matemátca, Uversdad Nacoal

More information

KURODA S METHOD FOR CONSTRUCTING CONSISTENT INPUT-OUTPUT DATA SETS. Peter J. Wilcoxen. Impact Research Centre, University of Melbourne.

KURODA S METHOD FOR CONSTRUCTING CONSISTENT INPUT-OUTPUT DATA SETS. Peter J. Wilcoxen. Impact Research Centre, University of Melbourne. KURODA S METHOD FOR CONSTRUCTING CONSISTENT INPUT-OUTPUT DATA SETS by Peter J. Wlcoxe Ipact Research Cetre, Uversty of Melboure Aprl 1989 Ths paper descrbes a ethod that ca be used to resolve cossteces

More information

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model Chapter 3 Asmptotc Theor ad Stochastc Regressors The ature of eplaator varable s assumed to be o-stochastc or fed repeated samples a regresso aalss Such a assumpto s approprate for those epermets whch

More information

Extreme Value Theory: An Introduction

Extreme Value Theory: An Introduction (correcto d Extreme Value Theory: A Itroducto by Laures de Haa ad Aa Ferrera Wth ths webpage the authors ted to form the readers of errors or mstakes foud the book after publcato. We also gve extesos for

More information

arxiv: v4 [math.nt] 14 Aug 2015

arxiv: v4 [math.nt] 14 Aug 2015 arxv:52.799v4 [math.nt] 4 Aug 25 O the propertes of terated bomal trasforms for the Padova ad Perr matrx sequeces Nazmye Ylmaz ad Necat Tasara Departmet of Mathematcs, Faculty of Scece, Selcu Uversty,

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

Parameter, Statistic and Random Samples

Parameter, Statistic and Random Samples Parameter, Statstc ad Radom Samples A parameter s a umber that descrbes the populato. It s a fxed umber, but practce we do ot kow ts value. A statstc s a fucto of the sample data,.e., t s a quatty whose

More information

Performance of a Queuing System with Exceptional Service

Performance of a Queuing System with Exceptional Service Iteratoal Joural o Eeer ad Matheatcal Sceces Ja.- Jue 0, Volue, Issue, pp.66-79 ISSN Prt 39-4537, Ole 39-4545. All rhts reserved www.jes.or IJEMS Abstract Perorace o a Queu Syste wth Exceptoal Servce Dr.

More information

MAX-MIN AND MIN-MAX VALUES OF VARIOUS MEASURES OF FUZZY DIVERGENCE

MAX-MIN AND MIN-MAX VALUES OF VARIOUS MEASURES OF FUZZY DIVERGENCE merca Jr of Mathematcs ad Sceces Vol, No,(Jauary 0) Copyrght Md Reader Publcatos wwwjouralshubcom MX-MIN ND MIN-MX VLUES OF VRIOUS MESURES OF FUZZY DIVERGENCE RKTul Departmet of Mathematcs SSM College

More information

Connective Eccentricity Index of Some Thorny Graphs

Connective Eccentricity Index of Some Thorny Graphs Aals of ure ad Appled Matheatcs Vol. 7, No., 04, 59-64 IN: 79-087X (), 79-0888(ole) ublshed o 9 epteber 04 www.researchathsc.org Aals of oectve Eccetrcty Idex of oe Thory raphs Nlaja De, k. Md. Abu Nayee

More information

Order Nonlinear Vector Differential Equations

Order Nonlinear Vector Differential Equations It. Joural of Math. Aalyss Vol. 3 9 o. 3 39-56 Coverget Power Seres Solutos of Hgher Order Nolear Vector Dfferetal Equatos I. E. Kougas Departet of Telecoucato Systes ad Networs Techologcal Educatoal Isttute

More information

ROOT-LOCUS ANALYSIS. Lecture 11: Root Locus Plot. Consider a general feedback control system with a variable gain K. Y ( s ) ( ) K

ROOT-LOCUS ANALYSIS. Lecture 11: Root Locus Plot. Consider a general feedback control system with a variable gain K. Y ( s ) ( ) K ROOT-LOCUS ANALYSIS Coder a geeral feedback cotrol yte wth a varable ga. R( Y( G( + H( Root-Locu a plot of the loc of the pole of the cloed-loop trafer fucto whe oe of the yte paraeter ( vared. Root locu

More information

Growth of a Class of Plurisubharmonic Function in a Unit Polydisc I

Growth of a Class of Plurisubharmonic Function in a Unit Polydisc I Issue, Volue, 7 5 Growth of a Class of Plursubharoc Fucto a Ut Polydsc I AITASU SINHA Abstract The Growth of a o- costat aalytc fucto of several coplex varables s a very classcal cocept, but for a fte

More information

International Journal of Mathematical Archive-3(12), 2012, Available online through ISSN

International Journal of Mathematical Archive-3(12), 2012, Available online through   ISSN teratoal Joural of Matheatal Arhve-3(2) 22 4789-4796 Avalable ole through www.ja.fo SSN 2229 546 g-quas FH-losed spaes ad g-quas CH-losed spaes Sr. Paule Mary Hele Assoate Professor Nrala College Cobatore

More information

The Lie Algebra of Smooth Sections of a T-bundle

The Lie Algebra of Smooth Sections of a T-bundle IST Iteratoal Joural of Egeerg Scece, Vol 7, No3-4, 6, Page 8-85 The Le Algera of Smooth Sectos of a T-udle Nadafhah ad H R Salm oghaddam Astract: I ths artcle, we geeralze the cocept of the Le algera

More information

Correlation of Neutrosophic Sets in Probability Spaces

Correlation of Neutrosophic Sets in Probability Spaces JMSI 10 014 No. 1 45 orrelato of Neutrosophc Sets Probablty Spaces I.M. HNFY.. SLM O. M. KHLED ND K. M. MHFOUZ bstract I ths paper we troduce ad study the cocepts of correlato ad correlato coeffcet of

More information

Interval extension of Bézier curve

Interval extension of Bézier curve WSEAS TRANSACTIONS o SIGNAL ROCESSING Jucheg L Iterval exteso of Bézer curve JUNCHENG LI Departet of Matheatcs Hua Uversty of Huates Scece ad Techology Dxg Road Loud cty Hua rovce 47 R CHINA E-al: ljucheg8@6co

More information

V. Hemalatha, V. Mohana Selvi,

V. Hemalatha, V. Mohana Selvi, Iteratoal Joural of Scetfc & Egeerg Research, Volue 6, Issue, Noveber-0 ISSN - SUPER GEOMETRIC MEAN LABELING OF SOME CYCLE RELATED GRAPHS V Healatha, V Mohaa Selv, ABSTRACT-Let G be a graph wth p vertces

More information

Mahmud Masri. When X is a Banach algebra we show that the multipliers M ( L (,

Mahmud Masri. When X is a Banach algebra we show that the multipliers M ( L (, O Multlers of Orlcz Saces حول مضاعفات فضاءات ا ورلكس Mahmud Masr Mathematcs Deartmet,. A-Najah Natoal Uversty, Nablus, Paleste Receved: (9/10/000), Acceted: (7/5/001) Abstract Let (, M, ) be a fte ostve

More information

Lecture 8. A little bit of fun math Read: Chapter 7 (and 8) Finite Algebraic Structures

Lecture 8. A little bit of fun math Read: Chapter 7 (and 8) Finite Algebraic Structures Lecture 8 A lttle bt of fu ath Read: Chapter 7 (ad 8) Fte Algebrac Structures Groups Abela Cyclc Geerator Group order Rgs Felds Subgroups Euclda Algorth CRT (Chese Reader Theore) 2 GROUPs DEFINITION: A

More information

Some identities involving the partial sum of q-binomial coefficients

Some identities involving the partial sum of q-binomial coefficients Some dettes volvg the partal sum of -bomal coeffcets Bg He Departmet of Mathematcs, Shagha Key Laboratory of PMMP East Cha Normal Uversty 500 Dogchua Road, Shagha 20024, People s Republc of Cha yuhe00@foxmal.com

More information

9 U-STATISTICS. Eh =(m!) 1 Eh(X (1),..., X (m ) ) i.i.d

9 U-STATISTICS. Eh =(m!) 1 Eh(X (1),..., X (m ) ) i.i.d 9 U-STATISTICS Suppose,,..., are P P..d. wth CDF F. Our goal s to estmate the expectato t (P)=Eh(,,..., m ). Note that ths expectato requres more tha oe cotrast to E, E, or Eh( ). Oe example s E or P((,

More information

Generalization of the Dissimilarity Measure of Fuzzy Sets

Generalization of the Dissimilarity Measure of Fuzzy Sets Iteratoal Mathematcal Forum 2 2007 o. 68 3395-3400 Geeralzato of the Dssmlarty Measure of Fuzzy Sets Faramarz Faghh Boformatcs Laboratory Naobotechology Research Ceter vesa Research Isttute CECR Tehra

More information

Chapter 4 Multiple Random Variables

Chapter 4 Multiple Random Variables Revew for the prevous lecture: Theorems ad Examples: How to obta the pmf (pdf) of U = g (, Y) ad V = g (, Y) Chapter 4 Multple Radom Varables Chapter 44 Herarchcal Models ad Mxture Dstrbutos Examples:

More information

Lecture 3 Probability review (cont d)

Lecture 3 Probability review (cont d) STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto

More information

PRACTICAL CONSIDERATIONS IN HUMAN-INDUCED VIBRATION

PRACTICAL CONSIDERATIONS IN HUMAN-INDUCED VIBRATION PRACTICAL CONSIDERATIONS IN HUMAN-INDUCED VIBRATION Bars Erkus, 4 March 007 Itroducto Ths docuet provdes a revew of fudaetal cocepts structural dyacs ad soe applcatos hua-duced vbrato aalyss ad tgato of

More information

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

Unimodality Tests for Global Optimization of Single Variable Functions Using Statistical Methods

Unimodality Tests for Global Optimization of Single Variable Functions Using Statistical Methods Malaysa Umodalty Joural Tests of Mathematcal for Global Optmzato Sceces (): of 05 Sgle - 5 Varable (007) Fuctos Usg Statstcal Methods Umodalty Tests for Global Optmzato of Sgle Varable Fuctos Usg Statstcal

More information

2/20/2013. Topics. Power Flow Part 1 Text: Power Transmission. Power Transmission. Power Transmission. Power Transmission

2/20/2013. Topics. Power Flow Part 1 Text: Power Transmission. Power Transmission. Power Transmission. Power Transmission /0/0 Topcs Power Flow Part Text: 0-0. Power Trassso Revsted Power Flow Equatos Power Flow Proble Stateet ECEGR 45 Power Systes Power Trassso Power Trassso Recall that for a short trassso le, the power

More information

Journal of Mathematical Analysis and Applications

Journal of Mathematical Analysis and Applications J. Math. Aal. Appl. 365 200) 358 362 Cotets lsts avalable at SceceDrect Joural of Mathematcal Aalyss ad Applcatos www.elsever.com/locate/maa Asymptotc behavor of termedate pots the dfferetal mea value

More information

The k-nacci triangle and applications

The k-nacci triangle and applications Kuhapataakul & Aataktpasal, Coget Mathematcs 7, : 9 https://doorg/8/879 PURE MATHEMATICS RESEARCH ARTICLE The k-acc tragle ad applcatos Katapho Kuhapataakul * ad Porpawee Aataktpasal Receved: March 7 Accepted:

More information

STRONG CONSISTENCY OF LEAST SQUARES ESTIMATE IN MULTIPLE REGRESSION WHEN THE ERROR VARIANCE IS INFINITE

STRONG CONSISTENCY OF LEAST SQUARES ESTIMATE IN MULTIPLE REGRESSION WHEN THE ERROR VARIANCE IS INFINITE Statstca Sca 9(1999), 289-296 STRONG CONSISTENCY OF LEAST SQUARES ESTIMATE IN MULTIPLE REGRESSION WHEN THE ERROR VARIANCE IS INFINITE J Mgzhog ad Che Xru GuZhou Natoal College ad Graduate School, Chese

More information

Marcinkiewicz strong laws for linear statistics of ρ -mixing sequences of random variables

Marcinkiewicz strong laws for linear statistics of ρ -mixing sequences of random variables Aas da Academa Braslera de Cêcas 2006 784: 65-62 Aals of the Brazla Academy of Sceces ISSN 000-3765 www.scelo.br/aabc Marckewcz strog laws for lear statstcs of ρ -mxg sequeces of radom varables GUANG-HUI

More information

Coherent Potential Approximation

Coherent Potential Approximation Coheret Potetal Approxato Noveber 29, 2009 Gree-fucto atrces the TB forals I the tght bdg TB pcture the atrx of a Haltoa H s the for H = { H j}, where H j = δ j ε + γ j. 2 Sgle ad double uderles deote

More information

On Modified Interval Symmetric Single-Step Procedure ISS2-5D for the Simultaneous Inclusion of Polynomial Zeros

On Modified Interval Symmetric Single-Step Procedure ISS2-5D for the Simultaneous Inclusion of Polynomial Zeros It. Joural of Math. Aalyss, Vol. 7, 2013, o. 20, 983-988 HIKARI Ltd, www.m-hkar.com O Modfed Iterval Symmetrc Sgle-Step Procedure ISS2-5D for the Smultaeous Icluso of Polyomal Zeros 1 Nora Jamalud, 1 Masor

More information

Analyzing Fuzzy System Reliability Using Vague Set Theory

Analyzing Fuzzy System Reliability Using Vague Set Theory Iteratoal Joural of Appled Scece ad Egeerg 2003., : 82-88 Aalyzg Fuzzy System Relablty sg Vague Set Theory Shy-Mg Che Departmet of Computer Scece ad Iformato Egeerg, Natoal Tawa versty of Scece ad Techology,

More information

18.413: Error Correcting Codes Lab March 2, Lecture 8

18.413: Error Correcting Codes Lab March 2, Lecture 8 18.413: Error Correctg Codes Lab March 2, 2004 Lecturer: Dael A. Spelma Lecture 8 8.1 Vector Spaces A set C {0, 1} s a vector space f for x all C ad y C, x + y C, where we take addto to be compoet wse

More information

Solution of General Dual Fuzzy Linear Systems. Using ABS Algorithm

Solution of General Dual Fuzzy Linear Systems. Using ABS Algorithm Appled Mathematcal Sceces, Vol 6, 0, o 4, 63-7 Soluto of Geeral Dual Fuzzy Lear Systems Usg ABS Algorthm M A Farborz Aragh * ad M M ossezadeh Departmet of Mathematcs, Islamc Azad Uversty Cetral ehra Brach,

More information

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur

More information

Application of Generating Functions to the Theory of Success Runs

Application of Generating Functions to the Theory of Success Runs Aled Mathematcal Sceces, Vol. 10, 2016, o. 50, 2491-2495 HIKARI Ltd, www.m-hkar.com htt://dx.do.org/10.12988/ams.2016.66197 Alcato of Geeratg Fuctos to the Theory of Success Rus B.M. Bekker, O.A. Ivaov

More information

ANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK

ANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK Far East Joural of Appled Mathematcs Volume, Number, 2008, Pages Ths paper s avalable ole at http://www.pphm.com 2008 Pushpa Publshg House ANALYSIS ON THE NATURE OF THE ASI EQUATIONS IN SYNERGETI INTER-REPRESENTATION

More information

A NEW LOG-NORMAL DISTRIBUTION

A NEW LOG-NORMAL DISTRIBUTION Joural of Statstcs: Advaces Theory ad Applcatos Volume 6, Number, 06, Pages 93-04 Avalable at http://scetfcadvaces.co. DOI: http://dx.do.org/0.864/jsata_700705 A NEW LOG-NORMAL DISTRIBUTION Departmet of

More information

for each of its columns. A quick calculation will verify that: thus m < dim(v). Then a basis of V with respect to which T has the form: A

for each of its columns. A quick calculation will verify that: thus m < dim(v). Then a basis of V with respect to which T has the form: A Desty of dagoalzable square atrces Studet: Dael Cervoe; Metor: Saravaa Thyagaraa Uversty of Chcago VIGRE REU, Suer 7. For ths etre aer, we wll refer to V as a vector sace over ad L(V) as the set of lear

More information

On generalized fuzzy mean code word lengths. Department of Mathematics, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

On generalized fuzzy mean code word lengths. Department of Mathematics, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India merca Joural of ppled Mathematcs 04; (4): 7-34 Publshed ole ugust 30, 04 (http://www.scecepublshggroup.com//aam) do: 0.648/.aam.04004.3 ISSN: 330-0043 (Prt); ISSN: 330-006X (Ole) O geeralzed fuzzy mea

More information

( ) ( ) ( ( )) ( ) ( ) ( ) ( ) ( ) = ( ) ( ) + ( ) ( ) = ( ( )) ( ) + ( ( )) ( ) Review. Second Derivatives for f : y R. Let A be an m n matrix.

( ) ( ) ( ( )) ( ) ( ) ( ) ( ) ( ) = ( ) ( ) + ( ) ( ) = ( ( )) ( ) + ( ( )) ( ) Review. Second Derivatives for f : y R. Let A be an m n matrix. Revew + v, + y = v, + v, + y, + y, Cato! v, + y, + v, + y geeral Let A be a atr Let f,g : Ω R ( ) ( ) R y R Ω R h( ) f ( ) g ( ) ( ) ( ) ( ( )) ( ) dh = f dg + g df A, y y A Ay = = r= c= =, : Ω R he Proof

More information

Polyphase Filters. Section 12.4 Porat

Polyphase Filters. Section 12.4 Porat Polyphase Flters Secto.4 Porat .4 Polyphase Flters Polyphase s a way of dog saplg-rate coverso that leads to very effcet pleetatos. But ore tha that, t leads to very geeral vewpots that are useful buldg

More information

3.1 Introduction to Multinomial Logit and Probit

3.1 Introduction to Multinomial Logit and Probit ES3008 Ecooetrcs Lecture 3 robt ad Logt - Multoal 3. Itroducto to Multoal Logt ad robt 3. Estato of β 3. Itroducto to Multoal Logt ad robt The ultoal Logt odel s used whe there are several optos (ad therefore

More information