Classification of Rational Homotopy Type for 8-Cohomological Dimension Elliptic Spaces

Size: px
Start display at page:

Download "Classification of Rational Homotopy Type for 8-Cohomological Dimension Elliptic Spaces"

Transcription

1 Aves Pure Mthemts Publshe Ole Jury 0 ( Clssfto of Rtol Homotopy Type for -Cohomologl Dmeso Ellpt Spes Mohme Rh Hll Hss Lme My Isml Mmou Fulté es Sees Aï Cho Csbl Moroo Cetre Pégogque Régol Rbt Moroo Eml: {rhll hlmee}@hotmlom mmoumysml@gmlom Reeve September 0; revse November 0; epte November 5 0 ABSTRACT The fferet methos use to lssfy rtol homotopy types of mfols re geerl fstg vrous (see []) I ths pper we re tereste to prtulr se tht of smply oete ellpt spes eote X by s- m H X; X 0 ussg ts ohomologl meso Here we wll the suss the se whe Keywors: Rtol Homotopy Theory; Ellpt Spes; Clssfto; Rtol Homotopy Type; Mml Moel of Sullv Itrouto Let us frst rell some bs eftos of rtol homotopy theory A smply oete spe X s lle ellpt f both of H X; π X re fte meso tht ts ohomologl Euler-Por hr terst s gve s X: m H X; 0 We wll fx ths throughout ths pper The spe s lle rtol f π X s -vetor spe If t s ot by [] we ssote rtol smply oete spe eote verfyg X ; H X X H X X slgebrs π svetorspes The rtol homotopy type of X s efe s the homotopy type of ts rtolzto X Our purpose ths pper to gve omplete lssfto ths rtol m H X; X 0 homotopy type whe Prelmres The rtol homotopy theory ws foue the the e of the sxtes by Del Qulle Des Sullv Oe of the tehl gget of ths theory s the mml moel of Sullv t s free -ommuttve fferetl gre lgebr V ssote to y smply oete CW omplex X of fte type [] Here V s -gre vetor spe wth m V V < eomposble fferetl; tht mes V V ( oes ot hve ler prt) tht Correspog uthor 0 It s well ow tht the mml moel V etermes the rtol homotopy type of X the sese tht X V H X; H V slgebrs π svetorspes For exmple the mml moel of eve sphere s of the form x y wth x y x 0 y x H ; x x whle the mml moel of sphere s of the form x y wth y y 0 It wll be utle for our proofs to rell the reer ths smple propertes For homogeeous elemet x of V x eotes ts egree whh verfes the followg: xy x y y x; xy x y x xy (Lebz formul) I prtulr x 0 whe x s xy yx whe x s eve X : mv s lle the homotop 0 Euler-Por hrterst of X I [5] S Hlper hve show the followg: π H V Oe other oto tht we wll use throughout ths pper s the forml meso of X gve s f X : mx H X ; 0 We ow from [5] tht whe re the elemets of homogee- π () Copyrght 0 SRes

2 M R HILAL ET AL ous bss of V f X () eve Our proofs re essetly bse o ths equlty ombe wth other equlty estblshe by J Freler S Hlper [] tht eve f X f X Flly let us rell tht H X; stsfes the Por ulty tht mes tht the multplto H X; H X; H X; s o egeerte bler form (here f X eotes the so lle fumetl lss of H X; ) For the reer tereste by more etls bout the rtol homotopy theory we reomme the bs referee [] The M Theorem I ll the remer of ths pper X eotes smply oete ellpt spe wth m H X; 0 V wll eotes t mml moel Put bss for H X; wth the oto tht tht V wth The followg tble summrzes the lssfto of ts rtol homotopy type Rtol homotopy type of X f X fx # f X Lege s s p fx p p f X p p f X p p Y E E : the totl spe of the fber bule wth p q s bse spe () Lege: ) I [] I M Jmes hs troue the oept of reue prout whe X s bse spe He put X X X : X X x x x x : p p p ) From ths ostruto pple to eve sphere rses the Jmes sphere p stsfyg p H ; p The use of the eotto p mes mpltly tht s suppose to be eve As the most of our proofs wll be by otrto we wll mr suh proofs by (by otrto) ts begg by (QED) whe ts e I the sprt esre to smplfy the leture of ths pper we wll subve t o my propostos lemms theorems The frst oe s tht: Lemm There exsts 5 suh tht < Proof Suppose tht f X 5 0 The Cse Where 5 Proposto If 5 X hs the rtol homotopy type (rht) of wth f X Proof Se V We stgush two ses: ) s The 0 Let E be the vetor spe spe by If m E we te s bss of E Let b b homogeeous bss of omplemet of V wth b b b therefore b 0 b H V wht m- ples tht m H V 9 of X s wth 0 So the mml moel Ths s extly the mml moel of If me the there exst suh tht 0 the Aorg to the Por ulty we hve so 0 Ths s mpossble ) s eve The f X re bef X use tht 0 Therefore 0 there exst tree geertors b of V wth eve egrees suh tht b The eve b f X Copyrght 0 SRes

3 M R HILAL ET AL Ths s mpossble The Cse Where 5 Lemm If 5 f X re eve s 0 Proof Frst beuse of the Por ulty we hve f X s eve hve 0 the sme prty Hee s s eve (By otrto) Suppose ow tht 0 se 0 the V Otherwse the Por ulty let us to suppose tht 5 to olue tht 5 tht re lso geertors of V So 5 5 f X f X Ths s mpossble (QED) Lemm If 5 there exsts homogeeous geertor b of V stsfyg b Proof Se 0 we ssume tht tht V Ot herwse there exsts homogeeous geertor b of V suh b Lemm 5 If 5 V x x x y D wth: Dx Dx Dy 0 Dy y xxy x x et y Proof We hve H V H W D W x x x y We efe the lgebr homomorph- sm : W D V s x x x b y s to beuse t trsforms the bss x x x y of W o the lerly epeet fmly b Let V0 W V V0 V se H V H V0 the V V V \ 0 0 Assume th t V 0 otht m x xv ser V suh x 0 b As 0 b 0 We hve to suss two ses: ; I th s se therefore eve b 9 > f X Ths s mpossble m m m 0 >5 > fx so 0 Let V suh I ths se V m s prtulr But 0 beuse f ot we wll hve m > fx Ths s mpossble Proposto If 5 the X hve oe of the followg rht: s fx # s X Proof Let us rell tht fx re eve tht re Frst se: 0 Se 0 the 0 0 Hee s bss for H X; therefore H X; b b e X hs the rht of Seo se: 0 Here re both o ull beuse the opposte se we wll hve b or b b s geertor of V ths ses 5 > f X Ths s mpossble Rep ths les us to olue tht X hve the rht of # The Cse Where 5 Proposto If 5 f f X s eve X hve the rht of p wth f X p Proof Beuse of the prty of fx the ulty of Por the ft tht 0 re respetve ly eve so 0 Assume tht 0 tht 5 there exst P P suh tht P P for 5 Ths mp les the mpossble stuto tht 0 but lso tht our seo ssumpto s flse Thus eessrly 5 re both geertors of V tht 5 > f X f X Ths other mpossble stuto mples tht our frst ssumpto s lso flse Put 0 ths se prtulr re geertors of V for The Por ulty let us to wrte to olue tht 0 tht 0 flly to wrte 5 Rell tht 0 beuse of the prty of the egree V b x wth b 0 x Ths s the mof p ml moel Copyrght 0 SRes

4 M R HILAL ET AL Proposto If 5 f fx s X hs oe of followg rht: p wth fx p p wth f X p p wth f X p Proof We wll suss three ses: Frst se: s 5 s eve Suppose eve tht 5 V eve 5 5 fx Ths s mpossble So wth 0 s egree geertor of V for or A sme ustfto s the lst proof let us to olue tht 5 p tht X hve the rht of Seo se: s eve 0 Se 5 s m Assume for exmple tht 0 wth or s Therefore 0 Let suppose tht re oller wrte 0 so 5 V Se tht 0 tht there exst two egree geertors of V b suh tht b We olue tht 5 b 5 f X > f X (mpossble) Put The mml moel of X wll be of the form V b b b wth 0 b b b 0 b p p e X Thr se: s eve 0 As the frst se we wrte 5 S e m Suppose tht 0 wrte ( 0 ) b e 0 Tht otrts the m hypothess our thr se Hee the mml moel of X wll be of the form V b b b wth b 0 b b e p X The Cse Whe re 5 Proposto 9 If 5 f X s eve x hve oe the rht of p Proof As f X s eve 0 re respetvely eve Suppose (by otrto) tht or s ull (for exmple 0) The ulty of Por sures tht 5 V 5 > f X Ths s mpossble (QED) Put 5 0 beuse tht Th s les us to te to olue tht 0 Hee V x y y y wth x y y 0 y x x y y p e p X Lemm 0 If 5 f X s 5 V Let us suppose V (for exmple) suss two ses: s eve 0 th ere exsts ge- ertor of V suh tht If s the >fx mpossble The s eve eessry m e there exsts geertor of V verfyg wth 0 or 0 Cosequetly fx wht s oe g mpossble stuto s beuse of the Por ulty we must hve be eve m Let 9 V suh tht 9 9 eve f X Ths s mpossble Lemm If 5 f X s 0 0 Proof (By otrto) Assume for exmple tht 0 By the preeet lemm the ulty of Por we hve Therefore 5 but f X s Ths s otrto (QED) Proposto If 5 f X s x h ve oe of the followg rht: wth Y Y hve mml Copyrght 0 SRes

5 M R HILAL ET AL 9 moel of the form b uv wth b 0 u b v b Proof By the two lst lemms we hve s V 0 V wth V But m H V (se lssfe by the frst uthor hs thess) X Y Y or Y Y V b u v b 0 u b v b 5 Cse Where 5 Lemm If 5 or Proof Suppose tht V there exst two geertors of V stsfyg 5 wth V We stgush two ses: Frst se: s eve s As f X s eve 0 s eve osequetly > fx eve Seo se: s As f X s eve 0 s eve fx eve The two ses re both mpossble Lemm If 5 : ) 0 ) ) V ) 5 Pro of ) suppose tht 0 s eve Se f X s eve 0 5 re both Put V 5 > f X (o trto) ) We hve If s eve s If s the result s evet beuse tht 0 ) It s mmete osequee of ) Hee we te 5 V Se ) 0 there exsts suh tht So Proposto 5 If 5 the X hve the hrt of or tht of Proof Put 5 the mml moel of X hve oe of the followg forms: V x y y y wth x y y 0 y x x y y e X V x y y y wth x y y 0 y x yy x y y e X Cse Where 5 Lemm If 5 5 Proof Let 5 V suss my ses: eve ) 5 V there exst two geertors x y of V suh tht x 5 y 5 ) s 9 > fx eve f X s e ve 0 eve s V > x y f X b) s eve As ) 5 V ) s eessry V 5 Hee there exsts geertor x o f V suh tht x 5 eve ) V re both se 0 Se 0 the V for or wth 0 5 Hee there exsts geert or y of V suh tht y so 5 > x y f X o ) V x V x > f X b) s eve eve eessr eve ) V y xv > eve x f X ) ulty) 5 0 the for or ( 0) 5 0 (Por ulty) Let x be geertor of V suh tht x 5 0 (beuse of the Por Put 5 V 5 5 x 5 fx > Lemm If 5 Proof Let V suss my ses: eve ) V The there exst geertors of Copyrght 0 SRes

6 0 M R HILAL ET AL V suh tht ) s eve f X f X > f X b) s > eve f X ) V eve ) V b) V t > f 9 X eve he >f 9 X Lemm If 5 V Proof Put N V ) If N th e for ll ths mples the otrto 0 ) I f N We hve ) re bot h eve th e f X s eve 0 Let be some ge ertors of V wth therefore > f X b) re both f X s 0 so (for exmple) s >fx ) s eve s o (for exmple) > eve f X Lemm 9 If 5 f V hve fferet prtes V Proof Suppose tht hve the sme prty ) If re both eve ll re eve for 0 ) If re eessry (beuse tht ) but ths s mpos sble Proposto 0 If 5 f V m X Proof Put V Beus e the ulty of Por the ft tht hve fferet prtes the ft tht for ll Let suh tht s m t s evet tht s eve As H V m 0 Ths llows us to te p p wth p beuse f ot m H V Hee 0 0 Colue tht V 0 W tht m V eve tht m H W I [?] W s the l of m mml mo e () X () m Lemm If 5 f V oly oe m og or s V Proof Assume tht V re both eve beuse tht eessry There- fore f X 0 e f X s there exsts ge ertor of V suh t ht wth eve > f X Lemm If 5 f V V Proof Suppose 0 we ow from the ulty of Por tht 5 by the Lemms tht 5 We eue tht 5 tht w here ) If 5 As 5 5 so s eve for ll but ths mples tht 0 ) If eessry 0 Hee fx 5 Se re both eve the f X So s eve fo r ll but ths les to the otrto 0 ) If 0 Suppose tht 0 suss two se s ) re eve 0 b) 5 f X s eve but lso f X s eve Therefore s eve for ll 0 ) If 0 (P or ulty) Hee 5 f X So < Proposto If 5 f V X hve o e of the followg rht: p E: the totl spe of the fber bule wth Copyrght 0 SRes

7 M R HILAL ET AL e wher e re both eve Proof We ow by the preeet lemms by the Por ulty tht Put 5 0 W e stgush two ses: ) 0 re both beuse tht 0 Reple by put the mml moel of X s of the form x y y y wth y p < x < y q y x yy Hee X ~ E p q E s fbrto of the KS-omplex q s bse sp y y 0 y y x y ) 0 X hve the mml moel x y y y wth y y 0 y x e X wth re both eve Aowlegemets xy The uthors woul le to th the oymous revewers for ther ostrutve ommets sutble ves o erler rft of ths ppe r It s lso plesure to th Pul Goerss Kthry Hess for ther terest egrteful to Hroo Shg ourgemet The uthors re Toshhro Ymguh for the severl eml susso exhge before the submsso of ths pper REFERENCES [] G Bzzo V Muõz Rtol Homotopy Type of Nlmfols Up to Dmeso rxv: 000v 00 [] J B Freler S Hlper A Arthmet Chrterzto of the Rtol Homotopy Groups of Cert Spes Ivetoes Mthemte Vol 5 No 99 pp - o:000/bf09009 [] Y Felx S Hlper J-C Thoms Rtol Homotopy Theory Grute Texts Mthemts Vol 05 Sprger-Verlg New Yor 00 [] P Grffths J Morg Rtol Homotopy Theory Dfferetl Forms Progress Mthemts Brhäuser Bsel 9 [5] S Hlper Ftess the Mml Moels of Sullv Trstos of Amer Mthemtl Soety Vol 0 9 pp -99 [] I M Jmes Reue Prout Spes Als of Mthemts Vol No 955 pp 0-9 o:00/000 [] G M L Powell Ellpt Spes wth the Rtol Homotopy Type of Spheres Bullet of the Belg Mthemtl Soety Smo Stev Vol No 99 pp 5- [] H Shg T Ymguh The Set of Rtol Homotopy Types wth Gve Cohomology Algebr Homology Homotopy Appltos Vol 5 No 00 pp - Copyrght 0 SRes

1 4 6 is symmetric 3 SPECIAL MATRICES 3.1 SYMMETRIC MATRICES. Defn: A matrix A is symmetric if and only if A = A, i.e., a ij =a ji i, j. Example 3.1.

1 4 6 is symmetric 3 SPECIAL MATRICES 3.1 SYMMETRIC MATRICES. Defn: A matrix A is symmetric if and only if A = A, i.e., a ij =a ji i, j. Example 3.1. SPECIAL MATRICES SYMMETRIC MATRICES Def: A mtr A s symmetr f d oly f A A, e,, Emple A s symmetr Def: A mtr A s skew symmetr f d oly f A A, e,, Emple A s skew symmetr Remrks: If A s symmetr or skew symmetr,

More information

Chapter 1 Vector Spaces

Chapter 1 Vector Spaces Chpter Vetor pes - Vetor pes Ler Comtos Vetor spe V V s set over fel F f V F! + V. Eg. R s vetor spe. For R we hek -4=-4-4R -7=-7-7R et. Eg. how tht the set of ll polomls PF wth oeffets from F s vetor

More information

Matrix. Definition 1... a1 ... (i) where a. are real numbers. for i 1, 2,, m and j = 1, 2,, n (iii) A is called a square matrix if m n.

Matrix. Definition 1... a1 ... (i) where a. are real numbers. for i 1, 2,, m and j = 1, 2,, n (iii) A is called a square matrix if m n. Mtrx Defto () s lled order of m mtrx, umer of rows ( 橫行 ) umer of olums ( 直列 ) m m m where j re rel umers () B j j for,,, m d j =,,, () s lled squre mtrx f m (v) s lled zero mtrx f (v) s lled detty mtrx

More information

CHAPTER 5 Vectors and Vector Space

CHAPTER 5 Vectors and Vector Space HAPTE 5 Vetors d Vetor Spe 5. Alger d eometry of Vetors. Vetor A ordered trple,,, where,, re rel umers. Symol:, B,, A mgtude d dreto.. Norm of vetor,, Norm =,, = = mgtude. Slr multplto Produt of slr d

More information

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek Optmlt of Strteges for Collpsg Expe Rom Vrles Smple Rom Smple E Stek troucto We revew the propertes of prectors of ler comtos of rom vrles se o rom vrles su-spce of the orgl rom vrles prtculr, we ttempt

More information

5 - Determinants. r r. r r. r r. r s r = + det det det

5 - Determinants. r r. r r. r r. r s r = + det det det 5 - Detemts Assote wth y sque mtx A thee s ume lle the etemt of A eote A o et A. Oe wy to efe the etemt, ths futo fom the set of ll mtes to the set of el umes, s y the followg thee popetes. All mtes elow

More information

CHAPTER 7 SOLVING FUZZY LINEAR FRACTIONAL PROGRAMMING PROBLEM BY USING TAYLOR'S SERIES METHOD

CHAPTER 7 SOLVING FUZZY LINEAR FRACTIONAL PROGRAMMING PROBLEM BY USING TAYLOR'S SERIES METHOD 67 CHAPTER 7 SOLVING FUZZY LINEAR FRACTIONAL PROGRAMMING PROBLEM BY USING TAYLOR'S SERIES METHOD 7. INTRODUCTION The eso mers the setors le fl ororte lg routo lg mretg me seleto uversty lg stuet mssos

More information

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ]

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ] Atervtves The Itegrl Atervtves Ojectve: Use efte tegrl otto for tervtves. Use sc tegrto rules to f tervtves. Aother mportt questo clculus s gve ervtve f the fucto tht t cme from. Ths s the process kow

More information

GENERALIZED OPERATIONAL RELATIONS AND PROPERTIES OF FRACTIONAL HANKEL TRANSFORM

GENERALIZED OPERATIONAL RELATIONS AND PROPERTIES OF FRACTIONAL HANKEL TRANSFORM S. Res. Chem. Commu.: (3 8-88 ISSN 77-669 GENERLIZED OPERTIONL RELTIONS ND PROPERTIES OF FRCTIONL NKEL TRNSFORM R. D. TYWDE *. S. GUDDE d V. N. MLLE b Pro. Rm Meghe Isttute o Teholog & Reserh Bder MRVTI

More information

Chapter 7. Bounds for weighted sums of Random Variables

Chapter 7. Bounds for weighted sums of Random Variables Chpter 7. Bouds for weghted sums of Rdom Vrbles 7. Itroducto Let d 2 be two depedet rdom vrbles hvg commo dstrbuto fucto. Htczeko (998 d Hu d L (2000 vestgted the Rylegh dstrbuto d obted some results bout

More information

Lecture 3: Review of Linear Algebra and MATLAB

Lecture 3: Review of Linear Algebra and MATLAB eture 3: Revew of er Aler AAB Vetor mtr otto Vetors tres Vetor spes er trsformtos Eevlues eevetors AAB prmer Itrouto to Ptter Reoto Rro Guterrez-su Wrht Stte Uverst Vetor mtr otto A -mesol (olum) vetor

More information

Data Compression Techniques (Spring 2012) Model Solutions for Exercise 4

Data Compression Techniques (Spring 2012) Model Solutions for Exercise 4 58487 Dt Compressio Tehiques (Sprig 0) Moel Solutios for Exerise 4 If you hve y fee or orretios, plese ott jro.lo t s.helsii.fi.. Prolem: Let T = Σ = {,,, }. Eoe T usig ptive Huffm oig. Solutio: R 4 U

More information

Available online through

Available online through Avlble ole through wwwmfo FIXED POINTS FOR NON-SELF MAPPINGS ON CONEX ECTOR METRIC SPACES Susht Kumr Moht* Deprtmet of Mthemtcs West Begl Stte Uverst Brst 4 PrgsNorth) Kolt 76 West Begl Id E-ml: smwbes@yhoo

More information

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares Itertol Jourl of Scetfc d Reserch Publctos, Volume, Issue, My 0 ISSN 0- A Techque for Costructg Odd-order Mgc Squres Usg Bsc Lt Squres Tomb I. Deprtmet of Mthemtcs, Mpur Uversty, Imphl, Mpur (INDIA) tombrom@gml.com

More information

On Several Inequalities Deduced Using a Power Series Approach

On Several Inequalities Deduced Using a Power Series Approach It J Cotemp Mth Sceces, Vol 8, 203, o 8, 855-864 HIKARI Ltd, wwwm-hrcom http://dxdoorg/02988/jcms2033896 O Severl Iequltes Deduced Usg Power Seres Approch Lored Curdru Deprtmet of Mthemtcs Poltehc Uversty

More information

A Study on Root Properties of Super Hyperbolic GKM algebra

A Study on Root Properties of Super Hyperbolic GKM algebra Stuy on Root Popetes o Supe Hypebol GKM lgeb G.Uth n M.Pyn Deptment o Mthemts Phypp s College Chenn Tmlnu In. bstt: In ths ppe the Supe hypebol genelze K-Mooy lgebs o nente type s ene n the mly s lso elte.

More information

3/20/2013. Splines There are cases where polynomial interpolation is bad overshoot oscillations. Examplef x. Interpolation at -4,-3,-2,-1,0,1,2,3,4

3/20/2013. Splines There are cases where polynomial interpolation is bad overshoot oscillations. Examplef x. Interpolation at -4,-3,-2,-1,0,1,2,3,4 // Sples There re ses where polyoml terpolto s d overshoot oslltos Emple l s Iterpolto t -,-,-,-,,,,,.... - - - Ide ehd sples use lower order polyomls to oet susets o dt pots mke oetos etwee djet sples

More information

Chapter Gauss-Seidel Method

Chapter Gauss-Seidel Method Chpter 04.08 Guss-Sedel Method After redg ths hpter, you should be ble to:. solve set of equtos usg the Guss-Sedel method,. reogze the dvtges d ptflls of the Guss-Sedel method, d. determe uder wht odtos

More information

Asymptotic Dominance Problems. is not constant but for n 0, f ( n) 11. 0, so that for n N f

Asymptotic Dominance Problems. is not constant but for n 0, f ( n) 11. 0, so that for n N f Asymptotc Domce Prolems Dsply ucto : N R tht s Ο( ) ut s ot costt 0 = 0 The ucto ( ) = > 0 s ot costt ut or 0, ( ) Dee the relto " " o uctos rom N to R y g d oly = Ο( g) Prove tht s relexve d trstve (Recll:

More information

The z-transform. LTI System description. Prof. Siripong Potisuk

The z-transform. LTI System description. Prof. Siripong Potisuk The -Trsform Prof. Srpog Potsuk LTI System descrpto Prevous bss fucto: ut smple or DT mpulse The put sequece s represeted s ler combto of shfted DT mpulses. The respose s gve by covoluto sum of the put

More information

MTH 146 Class 7 Notes

MTH 146 Class 7 Notes 7.7- Approxmte Itegrto Motvto: MTH 46 Clss 7 Notes I secto 7.5 we lered tht some defte tegrls, lke x e dx, cot e wrtte terms of elemetry fuctos. So, good questo to sk would e: How c oe clculte somethg

More information

ON NILPOTENCY IN NONASSOCIATIVE ALGEBRAS

ON NILPOTENCY IN NONASSOCIATIVE ALGEBRAS Jourl of Algebr Nuber Theory: Advces d Applctos Volue 6 Nuber 6 ges 85- Avlble t http://scetfcdvces.co. DOI: http://dx.do.org/.864/t_779 ON NILOTENCY IN NONASSOCIATIVE ALGERAS C. J. A. ÉRÉ M. F. OUEDRAOGO

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 Mtr Trsformtos usg Egevectors September 8, Mtr Trsformtos Usg Egevectors Lrry Cretto Mechcl Egeerg A Semr Egeerg Alyss September 8, Outle Revew lst lecture Trsformtos wth mtr of egevectors: = - A ermt

More information

Union, Intersection, Product and Direct Product of Prime Ideals

Union, Intersection, Product and Direct Product of Prime Ideals Globl Jourl of Pure d Appled Mthemtcs. ISSN 0973-1768 Volume 11, Number 3 (2015), pp. 1663-1667 Reserch Id Publctos http://www.rpublcto.com Uo, Itersecto, Product d Drect Product of Prme Idels Bdu.P (1),

More information

Chapter 9 Jordan Block Matrices

Chapter 9 Jordan Block Matrices Chapter 9 Jorda Block atrces I ths chapter we wll solve the followg problem. Gve a lear operator T fd a bass R of F such that the matrx R (T) s as smple as possble. f course smple s a matter of taste.

More information

Sequences and summations

Sequences and summations Lecture 0 Sequeces d summtos Istructor: Kgl Km CSE) E-ml: kkm0@kokuk.c.kr Tel. : 0-0-9 Room : New Mleum Bldg. 0 Lb : New Egeerg Bldg. 0 All sldes re bsed o CS Dscrete Mthemtcs for Computer Scece course

More information

Maximum Walk Entropy Implies Walk Regularity

Maximum Walk Entropy Implies Walk Regularity Maxmum Walk Etropy Imples Walk Regularty Eresto Estraa, a José. e la Peña Departmet of Mathematcs a Statstcs, Uversty of Strathclye, Glasgow G XH, U.K., CIMT, Guaajuato, Mexco BSTRCT: The oto of walk etropy

More information

Section 2.2. Matrix Multiplication

Section 2.2. Matrix Multiplication Mtri Alger Mtri Multiplitio Setio.. Mtri Multiplitio Mtri multiplitio is little more omplite th mtri itio or slr multiplitio. If A is the prout A of A is the ompute s follow: m mtri, the is k mtri, 9 m

More information

Chapter 3. Differentiation 3.3 Differentiation Rules

Chapter 3. Differentiation 3.3 Differentiation Rules 3.3 Dfferetato Rules 1 Capter 3. Dfferetato 3.3 Dfferetato Rules Dervatve of a Costat Fucto. If f as te costat value f(x) = c, te f x = [c] = 0. x Proof. From te efto: f (x) f(x + ) f(x) o c c 0 = 0. QED

More information

Lecture 1 - Introduction and Basic Facts about PDEs

Lecture 1 - Introduction and Basic Facts about PDEs * 18.15 - Introdution to PDEs, Fll 004 Prof. Gigliol Stffilni Leture 1 - Introdution nd Bsi Fts bout PDEs The Content of the Course Definition of Prtil Differentil Eqution (PDE) Liner PDEs VVVVVVVVVVVVVVVVVVVV

More information

Chapter 2. LOGARITHMS

Chapter 2. LOGARITHMS Chpter. LOGARITHMS Dte: - 009 A. INTRODUCTION At the lst hpter, you hve studied bout Idies d Surds. Now you re omig to Logrithms. Logrithm is ivers of idies form. So Logrithms, Idies, d Surds hve strog

More information

Riemann Integral Oct 31, such that

Riemann Integral Oct 31, such that Riem Itegrl Ot 31, 2007 Itegrtio of Step Futios A prtitio P of [, ] is olletio {x k } k=0 suh tht = x 0 < x 1 < < x 1 < x =. More suitly, prtitio is fiite suset of [, ] otiig d. It is helpful to thik of

More information

Design maintenanceand reliability of engineering systems: a probability based approach

Design maintenanceand reliability of engineering systems: a probability based approach Desg mateaead relablty of egeerg systems: a probablty based approah CHPTER 2. BSIC SET THEORY 2.1 Bas deftos Sets are the bass o whh moder probablty theory s defed. set s a well-defed olleto of objets.

More information

SUM PROPERTIES FOR THE K-LUCAS NUMBERS WITH ARITHMETIC INDEXES

SUM PROPERTIES FOR THE K-LUCAS NUMBERS WITH ARITHMETIC INDEXES Avlble ole t http://sc.org J. Mth. Comput. Sc. 4 (04) No. 05-7 ISSN: 97-507 SUM PROPERTIES OR THE K-UCAS NUMBERS WITH ARITHMETIC INDEXES BIJENDRA SINGH POOJA BHADOURIA AND OMPRAKASH SIKHWA * School of

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I Uversty o Hw ICS: Dscrete Mthemtcs or Computer Scece I Dept. Iormto & Computer Sc., Uversty o Hw J Stelovsy bsed o sldes by Dr. Be d Dr. Stll Orgls by Dr. M. P. Fr d Dr. J.L. Gross Provded by McGrw-Hll

More information

MATH 104: INTRODUCTORY ANALYSIS SPRING 2009/10 PROBLEM SET 8 SOLUTIONS. and x i = a + i. i + n(n + 1)(2n + 1) + 2a. (b a)3 6n 2

MATH 104: INTRODUCTORY ANALYSIS SPRING 2009/10 PROBLEM SET 8 SOLUTIONS. and x i = a + i. i + n(n + 1)(2n + 1) + 2a. (b a)3 6n 2 MATH 104: INTRODUCTORY ANALYSIS SPRING 2009/10 PROBLEM SET 8 SOLUTIONS 6.9: Let f(x) { x 2 if x Q [, b], 0 if x (R \ Q) [, b], where > 0. Prove tht b. Solutio. Let P { x 0 < x 1 < < x b} be regulr prtitio

More information

xl yl m n m n r m r m r r! The inner sum in the last term simplifies because it is a binomial expansion of ( x + y) r : e +.

xl yl m n m n r m r m r r! The inner sum in the last term simplifies because it is a binomial expansion of ( x + y) r : e +. Ler Trsfortos d Group Represettos Hoework #3 (06-07, Aswers Q-Q re further exerses oer dots, self-dot trsfortos, d utry trsfortos Q3-6 volve roup represettos Of these, Q3 d Q4 should e quk Q5 s espelly

More information

ES240 Solid Mechanics Z. Suo. Principal stress. . Write in the matrix notion, and we have

ES240 Solid Mechanics Z. Suo. Principal stress. . Write in the matrix notion, and we have ES4 Sold Mehs Z Suo Prpl stress Prpl Stress Imge mterl prtle stte o stress The stte o stress s xed, but we represet the mterl prtle my wys by uttg ubes deret orettos For y gve stte o stress, t s lwys possble

More information

A Brief Introduction to Olympiad Inequalities

A Brief Introduction to Olympiad Inequalities Ev Che Aprl 0, 04 The gol of ths documet s to provde eser troducto to olympd equltes th the stdrd exposto Olympd Iequltes, by Thoms Mldorf I ws motvted to wrte t by feelg gulty for gettg free 7 s o problems

More information

Exercise # 2.1 3, 7, , 3, , -9, 1, Solution: natural numbers are 3, , -9, 1, 2.5, 3, , , -9, 1, 2 2.5, 3, , -9, 1, , -9, 1, 2.

Exercise # 2.1 3, 7, , 3, , -9, 1, Solution: natural numbers are 3, , -9, 1, 2.5, 3, , , -9, 1, 2 2.5, 3, , -9, 1, , -9, 1, 2. Chter Chter Syste of Rel uers Tertg Del frto: The del frto whh Gve fte uers of dgts ts del rt s lled tertg del frto. Reurrg ( o-tertg )Del frto: The del frto (No tertg) whh soe dgts re reeted g d g the

More information

1.3 Continuous Functions and Riemann Sums

1.3 Continuous Functions and Riemann Sums mth riem sums, prt 0 Cotiuous Fuctios d Riem Sums I Exmple we sw tht lim Lower() = lim Upper() for the fuctio!! f (x) = + x o [0, ] This is o ccidet It is exmple of the followig theorem THEOREM Let f be

More information

SOME REMARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOMIAL ASYMPTOTE

SOME REMARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOMIAL ASYMPTOTE D I D A C T I C S O F A T H E A T I C S No (4) 3 SOE REARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOIAL ASYPTOTE Tdeusz Jszk Abstct I the techg o clculus, we cosde hozotl d slt symptote I ths ppe the

More information

The linear system. The problem: solve

The linear system. The problem: solve The ler syste The prole: solve Suppose A s vertle, the there ests uue soluto How to effetly opute the soluto uerlly??? A A A evew of dret ethods Guss elto wth pvotg Meory ost: O^ Coputtol ost: O^ C oly

More information

18.06 Problem Set 4 Due Wednesday, Oct. 11, 2006 at 4:00 p.m. in 2-106

18.06 Problem Set 4 Due Wednesday, Oct. 11, 2006 at 4:00 p.m. in 2-106 8. Problem Set Due Wenesy, Ot., t : p.m. in - Problem Mony / Consier the eight vetors 5, 5, 5,..., () List ll of the one-element, linerly epenent sets forme from these. (b) Wht re the two-element, linerly

More information

Chapter 2 Intro to Math Techniques for Quantum Mechanics

Chapter 2 Intro to Math Techniques for Quantum Mechanics Wter 3 Chem 356: Itroductory Qutum Mechcs Chpter Itro to Mth Techques for Qutum Mechcs... Itro to dfferetl equtos... Boudry Codtos... 5 Prtl dfferetl equtos d seprto of vrbles... 5 Itroducto to Sttstcs...

More information

Dual-Matrix Approach for Solving the Transportation Problem

Dual-Matrix Approach for Solving the Transportation Problem Itertol Jourl of Mthets Tres Tehology- Volue Nuer Jue 05 ul-mtr Aroh for Solvg the Trsortto Prole Vy Shr r Chr Bhus Shr ertet of Mthets, BBM College r, Jeh, (MU), INIA E-Prl, SS College Jeh, (MU), INIA

More information

Chapter 3. Differentiation 3.2 Differentiation Rules for Polynomials, Exponentials, Products and Quotients

Chapter 3. Differentiation 3.2 Differentiation Rules for Polynomials, Exponentials, Products and Quotients 3.2 Dfferetato Rules 1 Capter 3. Dfferetato 3.2 Dfferetato Rules for Polyomals, Expoetals, Proucts a Quotets Rule 1. Dervatve of a Costat Fucto. If f as te costat value f(x) = c, te f x = [c] = 0. x Proof.

More information

Preliminary Examinations: Upper V Mathematics Paper 1

Preliminary Examinations: Upper V Mathematics Paper 1 relmr Emtos: Upper V Mthemtcs per Jul 03 Emer: G Evs Tme: 3 hrs Modertor: D Grgortos Mrks: 50 INSTRUCTIONS ND INFORMTION Ths questo pper sts of 0 pges, cludg swer Sheet pge 8 d Iformto Sheet pges 9 d 0

More information

Connectivity in Graphs. CS311H: Discrete Mathematics. Graph Theory II. Example. Paths. Connectedness. Example

Connectivity in Graphs. CS311H: Discrete Mathematics. Graph Theory II. Example. Paths. Connectedness. Example Connetiit in Grphs CSH: Disrete Mthemtis Grph Theor II Instrtor: Işıl Dillig Tpil qestion: Is it possile to get from some noe to nother noe? Emple: Trin netork if there is pth from to, possile to tke trin

More information

DISCRETE TIME MODELS OF FORWARD CONTRACTS INSURANCE

DISCRETE TIME MODELS OF FORWARD CONTRACTS INSURANCE G Tstsshvl DSCRETE TME MODELS OF FORWARD CONTRACTS NSURANCE (Vol) 008 September DSCRETE TME MODELS OF FORWARD CONTRACTS NSURANCE GSh Tstsshvl e-ml: gurm@mdvoru 69004 Vldvosto Rdo str 7 sttute for Appled

More information

Math 140 Introductory Statistics

Math 140 Introductory Statistics Sttistics of Exm Mth Itrouctory Sttistics Professor B. Ábrego Lecture Sectios.3,.4 Me 7. SD.7 Mi 3 Q Me 7 Q3 8 Mx 0 0 0 0 0 0 70 80 0 Importt Uses of Coitiol Probbility To compre smplig with or without

More information

a f(x)dx is divergent.

a f(x)dx is divergent. Mth 250 Exm 2 review. Thursdy Mrh 5. Brig TI 30 lultor but NO NOTES. Emphsis o setios 5.5, 6., 6.2, 6.3, 3.7, 6.6, 8., 8.2, 8.3, prt of 8.4; HW- 2; Q-. Kow for trig futios tht 0.707 2/2 d 0.866 3/2. From

More information

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ]

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ] Are d the Defte Itegrl 1 Are uder Curve We wt to fd the re uder f (x) o [, ] y f (x) x The Prtto We eg y prttog the tervl [, ] to smller su-tervls x 0 x 1 x x - x -1 x 1 The Bsc Ide We the crete rectgles

More information

Modeling uncertainty using probabilities

Modeling uncertainty using probabilities S 1571 Itroduto to I Leture 23 Modelg uertty usg probbltes Mlos Huskreht mlos@s.ptt.edu 5329 Seott Squre dmstrto Fl exm: Deember 11 2006 12:00-1:50pm 5129 Seott Squre Uertty To mke dgost feree possble

More information

Counting Paths Between Vertices. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs

Counting Paths Between Vertices. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs Isomorphism of Grphs Definition The simple grphs G 1 = (V 1, E 1 ) n G = (V, E ) re isomorphi if there is ijetion (n oneto-one n onto funtion) f from V 1 to V with the property tht n re jent in G 1 if

More information

C.11 Bang-bang Control

C.11 Bang-bang Control Itroucto to Cotrol heory Iclug Optmal Cotrol Nguye a e -.5 C. Bag-bag Cotrol. Itroucto hs chapter eals wth the cotrol wth restrctos: s boue a mght well be possble to have scotutes. o llustrate some of

More information

CS 331 Design and Analysis of Algorithms. -- Divide and Conquer. Dr. Daisy Tang

CS 331 Design and Analysis of Algorithms. -- Divide and Conquer. Dr. Daisy Tang CS 33 Desig d Alysis of Algorithms -- Divide d Coquer Dr. Disy Tg Divide-Ad-Coquer Geerl ide: Divide problem ito subproblems of the sme id; solve subproblems usig the sme pproh, d ombie prtil solutios,

More information

MATH 104: INTRODUCTORY ANALYSIS SPRING 2008/09 PROBLEM SET 10 SOLUTIONS. f m. and. f m = 0. and x i = a + i. a + i. a + n 2. n(n + 1) = a(b a) +

MATH 104: INTRODUCTORY ANALYSIS SPRING 2008/09 PROBLEM SET 10 SOLUTIONS. f m. and. f m = 0. and x i = a + i. a + i. a + n 2. n(n + 1) = a(b a) + MATH 04: INTRODUCTORY ANALYSIS SPRING 008/09 PROBLEM SET 0 SOLUTIONS Throughout this problem set, B[, b] will deote the set of ll rel-vlued futios bouded o [, b], C[, b] the set of ll rel-vlued futios

More information

Analele Universităţii din Oradea, Fascicula: Protecţia Mediului, Vol. XIII, 2008

Analele Universităţii din Oradea, Fascicula: Protecţia Mediului, Vol. XIII, 2008 Alele Uverstăţ d Orde Fsul: Proteţ Medulu Vol. XIII 00 THEORETICAL AND COMPARATIVE STUDY REGARDING THE MECHANICS DISPLASCEMENTS UNDER THE STATIC LOADINGS FOR THE SQUARE PLATE MADE BY WOOD REFUSE AND MASSIF

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

Linear Algebra Concepts

Linear Algebra Concepts Ler Algebr Cocepts Ke Kreutz-Delgdo (Nuo Vscocelos) ECE 75A Wter 22 UCSD Vector spces Defto: vector spce s set H where ddto d sclr multplcto re defed d stsf: ) +( + ) (+ )+ 5) l H 2) + + H 6) 3) H, + 7)

More information

2. Elementary Linear Algebra Problems

2. Elementary Linear Algebra Problems . Eleety e lge Pole. BS: B e lge Suoute (Pog pge wth PCK) Su of veto opoet:. Coputto y f- poe: () () () (3) N 3 4 5 3 6 4 7 8 Full y tee Depth te tep log()n Veto updte the f- poe wth N : ) ( ) ( ) ( )

More information

Project 3: Using Identities to Rewrite Expressions

Project 3: Using Identities to Rewrite Expressions MAT 5 Projet 3: Usig Idetities to Rewrite Expressios Wldis I lger, equtios tht desrie properties or ptters re ofte lled idetities. Idetities desrie expressio e repled with equl or equivlet expressio tht

More information

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n 0. Sere I th ecto, we wll troduce ere tht wll be dcug for the ret of th chpter. Wht ere? If we dd ll term of equece, we get whch clled fte ere ( or jut ere) d deoted, for hort, by the ymbol or Doe t mke

More information

Advanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University

Advanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University Advced Algorthmc Prolem Solvg Le Arthmetc Fredrk Hetz Dept of Computer d Iformto Scece Lköpg Uversty Overvew Arthmetc Iteger multplcto Krtsu s lgorthm Multplcto of polyomls Fst Fourer Trsform Systems of

More information

Answer: First, I ll show how to find the terms analytically then I ll show how to use the TI to find them.

Answer: First, I ll show how to find the terms analytically then I ll show how to use the TI to find them. . CHAPTER 0 SEQUENCE, SERIES, d INDUCTION Secto 0. Seqece A lst of mers specfc order. E / Fd the frst terms : of the gve seqece: Aswer: Frst, I ll show how to fd the terms ltcll the I ll show how to se

More information

CH 45 INTRO TO FRACTIONS

CH 45 INTRO TO FRACTIONS CH INTRO TO FRACTIONS Itrotio W e re ot to erk o st of frtios. If o ve erstoo ritheti frtios efore, o ll fi tht lgeri frtios follo the se set of rles. If frtios re still ster, let s ke this the seester

More information

6.6 Moments and Centers of Mass

6.6 Moments and Centers of Mass th 8 www.tetodre.co 6.6 oets d Ceters of ss Our ojectve here s to fd the pot P o whch th plte of gve shpe lces horzotll. Ths pot s clled the ceter of ss ( or ceter of grvt ) of the plte.. We frst cosder

More information

The Number of Rows which Equal Certain Row

The Number of Rows which Equal Certain Row Interntonl Journl of Algebr, Vol 5, 011, no 30, 1481-1488 he Number of Rows whch Equl Certn Row Ahmd Hbl Deprtment of mthemtcs Fcult of Scences Dmscus unverst Dmscus, Sr hblhmd1@gmlcom Abstrct Let be X

More information

Definition Integral. over[ ab, ] the sum of the form. 2. Definite Integral

Definition Integral. over[ ab, ] the sum of the form. 2. Definite Integral Defiite Itegrl Defiitio Itegrl. Riem Sum Let f e futio efie over the lose itervl with = < < < = e ritrr prtitio i suitervl. We lle the Riem Sum of the futio f over[, ] the sum of the form ( ξ ) S = f Δ

More information

CS473-Algorithms I. Lecture 3. Solving Recurrences. Cevdet Aykanat - Bilkent University Computer Engineering Department

CS473-Algorithms I. Lecture 3. Solving Recurrences. Cevdet Aykanat - Bilkent University Computer Engineering Department CS473-Algorthms I Lecture 3 Solvg Recurreces Cevdet Aykt - Blket Uversty Computer Egeerg Deprtmet Solvg Recurreces The lyss of merge sort Lecture requred us to solve recurrece. Recurreces re lke solvg

More information

Two Coefficients of the Dyson Product

Two Coefficients of the Dyson Product Two Coeffcents of the Dyson Product rxv:07.460v mth.co 7 Nov 007 Lun Lv, Guoce Xn, nd Yue Zhou 3,,3 Center for Combntorcs, LPMC TJKLC Nnk Unversty, Tnjn 30007, P.R. Chn lvlun@cfc.nnk.edu.cn gn@nnk.edu.cn

More information

Solutions for HW9. Bipartite: put the red vertices in V 1 and the black in V 2. Not bipartite!

Solutions for HW9. Bipartite: put the red vertices in V 1 and the black in V 2. Not bipartite! Solutions for HW9 Exerise 28. () Drw C 6, W 6 K 6, n K 5,3. C 6 : W 6 : K 6 : K 5,3 : () Whih of the following re iprtite? Justify your nswer. Biprtite: put the re verties in V 1 n the lk in V 2. Biprtite:

More information

MATH34032: Green s Functions, Integral Equations and the Calculus of Variations 1. 1 [(y ) 2 + yy + y 2 ] dx,

MATH34032: Green s Functions, Integral Equations and the Calculus of Variations 1. 1 [(y ) 2 + yy + y 2 ] dx, MATH3403: Green s Funtions, Integrl Equtions nd the Clulus of Vritions 1 Exmples 5 Qu.1 Show tht the extreml funtion of the funtionl I[y] = 1 0 [(y ) + yy + y ] dx, where y(0) = 0 nd y(1) = 1, is y(x)

More information

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS PubH 745: REGRESSION ANALSIS REGRESSION IN MATRIX TERMS A mtr s dspl of umbers or umercl quttes ld out rectgulr rr of rows d colums. The rr, or two-w tble of umbers, could be rectgulr or squre could be

More information

Lesson 55 - Inverse of Matrices & Determinants

Lesson 55 - Inverse of Matrices & Determinants // () Review Lesson - nverse of Mtries & Determinnts Mth Honors - Sntowski - t this stge of stuying mtries, we know how to, subtrt n multiply mtries i.e. if Then evlute: () + B (b) - () B () B (e) B n

More information

Steady State Solution of the Kuramoto-Sivashinsky PDE J. C. Sprott

Steady State Solution of the Kuramoto-Sivashinsky PDE J. C. Sprott Stey Stte Soltio of the Krmoto-Sivshisy PDE J. C. Srott The Krmoto-Sivshisy etio is simle oe-imesiol rtil ifferetil etio PDE tht ehiits hos er some oitios. I its simlest form, the etio is give y t 0 where

More information

5. Solving recurrences

5. Solving recurrences 5. Solvig recurreces Time Complexity Alysis of Merge Sort T( ) 0 if 1 2T ( / 2) otherwise sortig oth hlves mergig Q. How to prove tht the ru-time of merge sort is O( )? A. 2 Time Complexity Alysis of Merge

More information

Learning Enhancement Team

Learning Enhancement Team Lernng Enhnement Tem Worsheet: The Cross Produt These re the model nswers for the worsheet tht hs questons on the ross produt etween vetors. The Cross Produt study gude. z x y. Loong t mge, you n see tht

More information

COMPLEX NUMBERS AND DE MOIVRE S THEOREM

COMPLEX NUMBERS AND DE MOIVRE S THEOREM COMPLEX NUMBERS AND DE MOIVRE S THEOREM OBJECTIVE PROBLEMS. s equl to b d. 9 9 b 9 9 d. The mgr prt of s 5 5 b 5. If m, the the lest tegrl vlue of m s b 8 5. The vlue of 5... s f s eve, f s odd b f s eve,

More information

arxiv:math/ v2 [math.ho] 16 Dec 2003

arxiv:math/ v2 [math.ho] 16 Dec 2003 rxiv:mth/0312293v2 [mth.ho] 16 Dec 2003 Clssicl Lebesgue Integrtion Theorems for the Riemnn Integrl Josh Isrlowitz 244 Ridge Rd. Rutherford, NJ 07070 jbi2@njit.edu Februry 1, 2008 Abstrct In this pper,

More information

On a class of analytic functions defined by Ruscheweyh derivative

On a class of analytic functions defined by Ruscheweyh derivative Lfe Scece Jourl ;9( http://wwwlfescecestecom O clss of lytc fuctos defed by Ruscheweyh dervtve S N Ml M Arf K I Noor 3 d M Rz Deprtmet of Mthemtcs GC Uversty Fslbd Pujb Pst Deprtmet of Mthemtcs Abdul Wl

More information

arxiv:math/ v1 [math.gm] 8 Dec 2005

arxiv:math/ v1 [math.gm] 8 Dec 2005 arxv:math/05272v [math.gm] 8 Dec 2005 A GENERALIZATION OF AN INEQUALITY FROM IMO 2005 NIKOLAI NIKOLOV The preset paper was spred by the thrd problem from the IMO 2005. A specal award was gve to Yure Boreko

More information

Math 426: Probability Final Exam Practice

Math 426: Probability Final Exam Practice Mth 46: Probbility Finl Exm Prctice. Computtionl problems 4. Let T k (n) denote the number of prtitions of the set {,..., n} into k nonempty subsets, where k n. Argue tht T k (n) kt k (n ) + T k (n ) by

More information

Fibonacci and Lucas Numbers as Tridiagonal Matrix Determinants

Fibonacci and Lucas Numbers as Tridiagonal Matrix Determinants Rochester Isttute of echology RI Scholr Wors Artcles 8-00 bocc d ucs Nubers s rdgol trx Deterts Nth D. Chll Est Kod Copy Drre Nry Rochester Isttute of echology ollow ths d ddtol wors t: http://scholrwors.rt.edu/rtcle

More information

Integral Operator Defined by k th Hadamard Product

Integral Operator Defined by k th Hadamard Product ITB Sci Vol 4 A No 35-5 35 Itegrl Opertor Deied by th Hdmrd Product Msli Drus & Rbh W Ibrhim School o Mthemticl Scieces Fculty o sciece d Techology Uiversiti Kebgs Mlysi Bgi 436 Selgor Drul Ehs Mlysi Emil:

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

Math 61CM - Solutions to homework 9

Math 61CM - Solutions to homework 9 Mth 61CM - Solutions to homework 9 Cédric De Groote November 30 th, 2018 Problem 1: Recll tht the left limit of function f t point c is defined s follows: lim f(x) = l x c if for ny > 0 there exists δ

More information

Pre-Lie algebras, rooted trees and related algebraic structures

Pre-Lie algebras, rooted trees and related algebraic structures Pre-Lie lgers, rooted trees nd relted lgeri strutures Mrh 23, 2004 Definition 1 A pre-lie lger is vetor spe W with mp : W W W suh tht (x y) z x (y z) = (x z) y x (z y). (1) Exmple 2 All ssoitive lgers

More information

Notes 17 Sturm-Liouville Theory

Notes 17 Sturm-Liouville Theory ECE 638 Fll 017 Dvid R. Jckso Notes 17 Sturm-Liouville Theory Notes re from D. R. Wilto, Dept. of ECE 1 Secod-Order Lier Differetil Equtios (SOLDE) A SOLDE hs the form d y dy 0 1 p ( x) + p ( x) + p (

More information

Lecture 3 ( ) (translated and slightly adapted from lecture notes by Martin Klazar)

Lecture 3 ( ) (translated and slightly adapted from lecture notes by Martin Klazar) Lecture 3 (5.3.2018) (trnslted nd slightly dpted from lecture notes by Mrtin Klzr) Riemnn integrl Now we define precisely the concept of the re, in prticulr, the re of figure U(, b, f) under the grph of

More information

Tail Factor Convergence in Sherman s Inverse Power Curve Loss Development Factor Model

Tail Factor Convergence in Sherman s Inverse Power Curve Loss Development Factor Model T tor Covergee Sherm s Iverse Power Curve Loss Deveopmet tor Moe Jo Evs Astrt The fte prout of the ge-to-ge eveopmet ftors Sherm s verse power urve moe s prove to overge to fte umer whe the power prmeter

More information

Patterns of Continued Fractions with a Positive Integer as a Gap

Patterns of Continued Fractions with a Positive Integer as a Gap IOSR Jourl of Mthemtcs (IOSR-JM) e-issn: 78-578, -ISSN: 39-765X Volume, Issue 3 Ver III (My - Ju 6), PP -5 wwwosrjourlsorg Ptters of Cotued Frctos wth Postve Iteger s G A Gm, S Krth (Mthemtcs, Govermet

More information

Hamilton s principle for non-holonomic systems

Hamilton s principle for non-holonomic systems Das Hamltosche Przp be chtholoome Systeme, Math. A. (935), pp. 94-97. Hamlto s prcple for o-holoomc systems by Georg Hamel Berl Traslate by: D. H. Delphech I the paper Le prcpe e Hamlto et l holoomsme,

More information

strt: I ths pper the trler oorte ple s stue s geerle to the -esol ule spe -ler oorte sste s estlshe The oplr theore of -pots the ourret theore of -hpe

strt: I ths pper the trler oorte ple s stue s geerle to the -esol ule spe -ler oorte sste s estlshe The oplr theore of -pots the ourret theore of -hpe -ler Coorte Sste Its ppltos Te Meer : Yu Xhg Teher : L Xhu The fflte Hgh Shool of South Ch Norl Uverst Pge - 3 strt: I ths pper the trler oorte ple s stue s geerle to the -esol ule spe -ler oorte sste

More information

ON JENSEN S AND HERMITE-HADAMARD S INEQUALITY

ON JENSEN S AND HERMITE-HADAMARD S INEQUALITY IJRRAS 7 3 Deemer 203 wwwrressom/volumes/vol7issue3/ijrras_7_3_02 ON JENSEN S AND HERMITE-HADAMARD S INEQUALITY Zlto Pvć & Ver Novosel 2 Mehl Egeerg Fulty Slvos Bro Uversty o Osje Trg Ive Brlć Mžurć 2

More information

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS . REVIEW OF PROPERTIES OF EIGENVLUES ND EIGENVECTORS. EIGENVLUES ND EIGENVECTORS We hll ow revew ome bc fct from mtr theory. Let be mtr. clr clled egevlue of f there et ozero vector uch tht Emle: Let 9

More information

Differential Method of Thin Layer for Retaining Wall Active Earth Pressure and Its Distribution under Seismic Condition Li-Min XU, Yong SUN

Differential Method of Thin Layer for Retaining Wall Active Earth Pressure and Its Distribution under Seismic Condition Li-Min XU, Yong SUN Itertol Coferece o Mechcs d Cvl Egeerg (ICMCE 014) Dfferetl Method of Th Lyer for Retg Wll Actve Erth Pressure d Its Dstrbuto uder Sesmc Codto L-M XU, Yog SUN Key Lbortory of Krst Evromet d Geologcl Hzrd

More information

The Basic Properties of the Integral

The Basic Properties of the Integral The Bsic Properties of the Itegrl Whe we compute the derivtive of complicted fuctio, like x + six, we usully use differetitio rules, like d [f(x)+g(x)] d f(x)+ d g(x), to reduce the computtio dx dx dx

More information

under the curve in the first quadrant.

under the curve in the first quadrant. NOTES 5: INTEGRALS Nme: Dte: Perod: LESSON 5. AREAS AND DISTANCES Are uder the curve Are uder f( ), ove the -s, o the dom., Prctce Prolems:. f ( ). Fd the re uder the fucto, ove the - s, etwee,.. f ( )

More information