Two kinds of B-basis of the algebraic hyperbolic space *

Size: px
Start display at page:

Download "Two kinds of B-basis of the algebraic hyperbolic space *"

Transcription

1 75 L e al. / J Zhejag Uv SCI 25 6A(7): Joual of Zhejag Uvesy SCIECE ISS h:// E-al: jzus@zju.edu.c Two ds of B-bass of he algebac hyebolc sace * LI Ya-jua ( 李亚娟 ) WAG Guo-zhao ( 汪国昭 ) (Deae of Maheacs Zhejag Uvesy Hagzhou 327 Cha) E-al: lyajua94@sohu.co Receved Oc ; evso acceed Dec Absac: I hs ae wo ew ds of B-bass fucos called algebac hyebolc (AH) Béze bass ad AH B-Sle bass ae eseed he sace Γ sa{ 3 shcosh} whch K s a abay ege lage ha o equal o 3. They shae os oal oees as hose of he Béze bass ad B-Sle bass esecvely ad ca eese exacly soe eaable cuves ad sufaces such as he hyebola caeay hyebolc sal ad he hyebolc aabolod. The geeao of eso oduc sufaces of he AH B-Sle bass have wo fos: AH B-Sle suface ad AH T-Sle suface. Key wods: Algebac hyebolc Béze bass Algebac hyebolc B-Sle bass Algebac hyebolc Béze cuve Algebac hyebolc B-Sle cuve do:.63/jzus.25.a75 Docue code: A CLC ube: TP39.72 ITRODUCTIO Béze bass ad B-Sle bass ae wo oa bases of he olyoal sace saed by { 2 } whch s a abay osve ege. Howeve as show by Maa e al. (2) hee sll exs seveal laos of Béze odel ad B-Sle odel. Che ad Wag (23) ad Wag e al.(24) cosuced C-Béze bass ad he o ufo algebac gooec (UAT) B-Sle bass of he sace saed by { 2 scos} whch ca eese exacly ascedeal cuves such as helx ad cyclod. Koch ad Lyche (99) eseed a d of exoeal sle. I hs ae we wll gve wo bases fo he algebac hyebolc sace Γ saed by { 3 shcosh} whch ca eese exacly soe eaable cuves such as he hyebola ad he caeay. ALGEBRAIC HYPERBOLIC (AH) BÉZIER BASIS * Pojecs suoed by he aoal aual Scece Foudao of Cha (o. 37) ad he aoal Basc Reseach Poga (973) of Cha (o.g22cb32) Defo of he AH Béze bass We fs ese he AH Béze bass fucos. The cosuco s ecusve sag wh he wo al fucos: sh( ) sh B() B() sh sh [ ] ( + ) () Fo > he AH Béze bass fucos {B B 2 B } of he sace Γ + saed by { sh cosh } ae defed ecusvely by: B () B ( s)ds B () ( B ( s) B ( s))ds B () B ( s)ds (2) whee B ( )d <<. The we ge he defo of he AH Béze bass: Defo {B B B } s called he AH

2 L e al. / J Zhejag Uv SCI 25 6A(7): Béze bass fo he sace Γ + saed by{ 2 sh cosh}. See Fg B 3 () B 3 () B () The lea deedece of he {B B B } wll be oved Seco 2. I acula f we use B () B () as he wo al fucos we ge he Béze bass fo he olyoal sace fo Eq.(2); f we use s o elace sh he al fucos we wll ge he C-Béze bass fo he algebac gooec sace fo Eq.(2). Poees of he AH Béze bass () Pao of uy By he defo of he AH Béze bass s easy o ove B () [] (+ )..2 (2) Syey B ()B ( ) fo []. Poof Cosde he suao whe he syey oey s obvous. Suose holds fo ; B () B ( ) We ow ove he oey by duco o : B ()d s s B ( s)ds ()d.4 B s s B ()d s s Leg we oba. Fo < < we have:.6 B ().8 B 33 () B 23 () Fg. AH Béze bass fucos of ode 2 ad 4 B ( ) B ( s)ds B ()d s s ( ( )d ) ( ( )d ) B s s B s s B () The oof fo he suao whe ad s sla. Tha s he syey oey s oved. (3) Poees of he edos A he edos he AH Béze bass has he sae oees as he Béze bass ad C-Béze bass. Tha s fo 2 (a) j j B () B ( ) (3) (b) B () B ( ) j (4) () (c) B () (5) (d) 2 2 ( ) ( ) 2 B (6) Eq.(5) ad Eq.(6) ca be oved by duco o. (4) Lea deedece Le ab () [ ]. By ag we ge fo Eq.(4) ha. Dffeeag he above foula es we deduce aga fo Eq.(4) ha fo. Theefoe B B B ae lea deede ad { B B B } s a bass of Γ +. (5) Degee elevao: Dffeeag + j j + j B () a B () es we have fo oey (3) of he AH Béze bass ha fo Thus: B () a B () + a B () (7) Usg L Hosal s Rule we have a B () a + B+ + () B () + B () a + B+ + () l + B () +

3 752 L e al. / J Zhejag Uv SCI 25 6A(7): ad a B () a B () l + B () + B () B () 2 2 () + () 2 + B ( ) ( ) 2 + ( ) B+ + ( ) whee { B ( )} s he AH Béze bass fo he sace Γ + ad s a global shae aaee. AH Béze cuve has ay oees he sae as hose of he Béze cuve: () Edos eolao ()P ()P. Fo oey () of he AH Béze bass we ow B () [ a B () + a B ()] B ( ) + By he lea deedece of he AH Béze bass we have a + a+ + I fac +. Thus we have he degee elevao foula: () ( + ) B () B () + B () B () () () () + + B + + B + () B+ + () Posvy B ()> fo () so AH Béze bass s a bledg syse. Poof Cosde a abay AH Béze basc fuco B () 2. By he Rolle s Theoe ad oey (4) of he AH Béze bass we deduce ha B () has ad oly has zeos a [] cludg he -fold zeo a ad he ( )-fold zeo a so B () s ehe osve o egave o he eval ( ). Fo oey (5) of he AH Béze bass we ge ha he AH Béze bass s osve fo (). AH Béze cuves A ode + AH Béze cuve () wh cool os s defed as: () B () [ ] ( + ) (8) (2) Covex hull oey The ee AH Béze cuve Eq.(8) us le sde s cool olygo saed by (Fg.2) (3) Devave The devave () of a AH Béze cuve Eq.(8) s clealy a ode cuve: q () B () [ ] whee q ( + ). I acula we have Fg.2 AH Béze cuve ad cool olygo ( ) ( ) B () () (4) Degee elevao By he elevao of he AH Béze bass fucos we gve he degee elevao of he AH Béze cuve easly as: + + () B () B () q (9) hee q () () B () B () q () -+ () B + () B + () q +

4 L e al. / J Zhejag Uv SCI 25 6A(7): I fac a degee elevao ocedue s a coe cug ocedue jus as hose of he Béze cuve. I ca be vefed ha he sequece of cool olygos we ge ecusvely fo Eq.(9) coveges o he AH Béze cuve. (5) Vaao dshg (V. D.) oey o lae esecs a AH Béze cuve oe ofe ha esecs he coesodg cool olygo. We wll ove Seco 3. (6) Covexy esevg oey If he cool olygo s covex he he coesodg AH Béze cuve s also covex. (7) The l of he AH Béze cuves As he l of a AH Béze cuve he sace Γ + aoaches a Béze cuve he sace saed by { 2 }. I Fg.3 Fg.3b s obaed by ag he evals ad oo he eval (a) Béze Poof Reaaezg by τ/ s easy o ove ha he esul holds fo. Suose holds fo ad by ducve hyohess: B () B ( τ ) l B ( τ ) b ( τ ) Béze (b) Fg.3 Béze cuve ad AH Béze cuve (a) fo ; (b) fo hee b (τ) τ s a Béze bass. We gve he oof by duco by : B ()d s s B ()d s s B () [ B () s B ()]d s s B ()d s s B ()d s s B B l B ( τ ) l B ( τ ) B ( τ ) ( τ )d τ ( τ )dτ b ( τ) b ( τ) b ( τ)d τ b ( τ)dτ b ( ( τ) b ( τ)) b ( τ ) By he oees (3) ad (4) of he AH Béze bass we have B ()b () heefoe: l B ( τ ) b ( τ ) Fo he defos of AH Béze cuve ad Béze cuve we ge he oey (8). (8) The AH Béze bass s B-bass By he oees () (5) ad (6) we have ha AH Béze bass s a oally osve bass. I s easy o ge f{b ()/B j () B j () } by L Hosal s Rule. Fo Pooso 3.2 (Cace ad Peña 994) AH Béze bass s B-bass so has oal shae esevg oees [Chae 4 of (Peña 999)] ad oal sably oees fo he evaluao [Chae 5 of (Peña 999)]. AH Béze suface A AH Béze suface ca be cosuced usg eso oduc: uv ( ) B ( ub ) ( v) j j j u [ ] v [ β] β ( + ) I whch B (u) B j (v) ae he AH Béze bass fucos ad j ae he cool os. I should be oed ha oe ca choose a dffee aaee β he v deco. Is oees ca be deduced by hose of he AH Béze cuve.

5 754 L e al. / J Zhejag Uv SCI 25 6A(7): ALGEBRAIC HYPERBOLIC B-SPLIE BASIS (AH B-SPLIE) Defo of he AH B-Sle bass + LeT be a gve o sequece { } wh + we fs gve a se of al fucos: sh( ) / sh( + ) < + 2( ) sh( + 2 ) / sh( ) + < + 2 ohewse () Hee we defe ha /. The he AH B-Sle bass fucos of ode he sace Γ sa { 3 shcosh} ca be defed ecusvely as: () ( ( s) ( s))ds () whee ( )d. If () ad (). We have fo Eq.() he followg: ()d s s < < + + so we ge he defo of he AH B-Sle: Defo 2 { + +2 } s called he AH B-Sle bass of he sace Γ saed by { 3 shcosh} fo [ + ]. The lea deedece of he { + +2 } wll be oved Seco 3. I acula f we elace sh by Eq.() we ge he B-Sle bass fo he olyoal sace fo Eq.(); f we elace sh by s Eq.() we wll ge he UAT B-Sle bass fo he algebac gooec sace fo Eq.(). If he o sequece s ufo we wll ge he ufo hyebolc olyoal B-Sle bass descbed (Lü e al. 22). The sequece of () has he followg oees jus he sae as hose of he B-Sle. Poees of he AH B-Sle bass () Local suo () [ + ]. (2) Pao of uy + () fo all 3 ad all. (3) Devave () () (). + + (4) Zeo fuco () f ad oly f + +. (5) Posvy ()> fo ( ). Hee <. () fo all. Ths ca be oved he sae way as ha fo AH Béze bass. (6) Dffeeal () s ( j ) e couously dffeeal a he o j wh j he ube of es j aeas + he o sequece { }. j (7) Le ax{s +s }. If 2 we he have: j j ( ) j (8) Lea deedece + () +2 () () ae lealy deede o [ + ] wh < + fo all 2. As a cosequece of hs we ge ha () ± ae lealy deede o (+ ) f ad oly f he ullcy of each o of T s less ha +. Tha s hee s o zeo fuco () ± (9) Relao wh AH Béze bass I he case + +2 < () () ae jus he AH Béze bass of ode o [ + ]. Fo he defos of he wo bases he above oey ca be oved by duco o. Iseg a ew o I s he sae as he B-Sle ad he UAT B-Sle we have he o seg heoe of he

6 L e al. / J Zhejag Uv SCI 25 6A(7): AH B-Sle: + Theoe Le T( ) be a gve o sequece wh + <+ ad le ( + T ) be a ew o sequece obaed by seg a ew o u o T wh u< + j () ad j () ae defed as Eq.() fo he o sequece T ad T esecvely. If s ae ullces of he os u T esecvely we have fo all j 2 j () j j () + β j + j + () (2) whee fo <: j j j j j < j < + j + j β j β j + j j+ < j < + j + ad fo j j + j β j j > j > + ad j sh( u ) j 2 j sh( + ) j + (3) j sh( + u) β j 2 j sh( + ) j + whe ad s we have + (Fg.4). + + ( ) Poof Le 2 we oba Eq.(3) by dec calculao. Suose he ooso holds fo : (+) Fg.4 Iseg a o a j () () + β () fo all j. j j j+ j+ ow we wll ove he case fo. By he defo we he have () () fo j ad j j+ j j () () fo j + whch les j β j+ fo j ad j β j+ fo j +. (). I s easy o ove ha j β j+ fo j ad j β j+ fo j +. (2) <. By assuo we have ( () () ) ( ) () ( () ())d j j j j+ j+ j j j β j+ j+ j+ j+ j+ j+ 2 j+ 2 () β () d A() + A2() + A3() fo + j whee j j A () j j j () j+ j+ ()d j j j () j j+ β j+ 2 A2 () j+ 2 ( j+ j+ ( ) j+ 2 j+ 2 ( ) d j+ βj+ 2 j+ () j+ 2 3 λ j + j + A () ()d wh λ soe eal ube. Le v we have j (v)a (v) A 2 (v) whle ν 3 j + j + A () v ()d fo + j. We ge ha λ so we oba β () () () j j j+ j+ 2 j j + j+ j j+ 2 fo + j.

7 756 L e al. / J Zhejag Uv SCI 25 6A(7): I eas β j j j j 2 j β + + j+ j j+ 2 fo + j. (3). Whe s he oof s sla o he case (2). If s s also sla o he case (2) fo +<j. Fo j + we have + (). We defe: ()d + + so we have + () + + ()d < ( ) ( ) ( ) d () β ( + ) d sla o he case (2) we have β () () + () Tha s β β Fo he dscusso above we ge ha he ooso also holds fo. Ths oves Theoe also gves a ehod o coue he coeffces j β j+ fo all j. Fuheoe By he oey of ao of uy ad he lealy deedece of () ± we have he foula j +β j fo all wh () fo all. The Eq.(2) ca be ewe as () () + ( + ) + () (4) ow we gve he oof of he o-egavy oey of () ± Theoe 2 () fo all. Poof By he local suo we have ha () ca be o-zeo oly o [ + ]. If + we have () fo oey (4). I he followg suose < + we se a sees of ew os o o sequece T such ha he ullcy of each o j (j +) s. We he oba a ew o sequece deoed by T. Le be he ew sles wh he ew o sequece T he () s a covex cobao of (). By oey (9) we have ha () deeed by j (j +) s acually a AH Béze bass o each eval [ j j+ ] j+ + j < j+. Thus we have () fo all. AH B-Sle cuves AH B-Sle bass () ± has ay good oees so ca be used fo geoec odellg. Because of he local suo oey we ca defe a ece of AH B-Sle cuve () wh cool os a fe eval such as [ + ] (Fg.5). 2 3 () () [ ] + (5) whee { ( )} s he AH B-Sle bass wh he o sequece T { } + fo he sace Γ. AH B-Sle cuve has ay oees he sae as hose of he B-Sle cuve: () Devave The devave () of a ode AH B-Sle cuve () s clealy a degee cuve: 5 Fg.5 A ece of AH B-Sle cuve 4

8 L e al. / J Zhejag Uv SCI 25 6A(7): () () ( ) ( ) [ ] + The + j j (8) j u ( ) ( u) (2) Local cool oey Chage of oe cool o wll ale a os seges of he ogal AH B-Sle cuve of ode. Hece local adjuse ca be ade whou dsubg he es of he cuve. (3) Geoec vaace The shae of he AH B-Sle cuve s deede of he choce of he coodae syse because () s a affe cobao of he cool os. (4) Covex hull oey The ee AH B-Sle cuve us le sde s cool olygo (Fg.5). I follows fo he oegave ad ao of uy of he AH B-Sle bass. (5) Dffeeal () s couously dffeeal a a o of ullcy. (6) Subdvso of he cuves Subsug Eq.(4) o Eq.(5) we have ( + + ) () () + ( ) () + () (6) whee ( ) + +. (7) wh ad () as defed Seco 3. Fo Eq.(7) we ge ha he ew cool os ca be obaed fo he old cool os afe subdvso. I fac he ocess of seg a ew o s acually a coe cug ocess. If we se he sae o u <u< + eavely he we wll ge a sees of ew l cool os +l fo Eq.(7). Hee l s he es of seg o. I acula whe l sce l j ( u) j j We use () o deoe a AH B-Sle cuve of ode wh Φ [ ] [ ] T T ( ) + as he cool olygo ad o sequece. Le T ( ) ++ be he ew o sequece obaed by seg a ew o o T ad Φ [ ] Φ[ Φ [ ]] [ + ] be he cool olygo whee he cool os + + ae gve by Eq.(7). Ad le ax ++. We have he followg heoe. Theoe 3 Whe as he ube of subdvsos ceases he sequece of cool olygos Φ [] coveges o he AH sle cuve (). Poof Le () be he AH B-Sle bass fucos wh he o sequece T. By he defo of Φ [] we have + + () () () [ ] Fo he oey () of he cuves we have + () () () [ ] + whee. I ca be easly see ha () s a ece of AH B-Sle cuve of ode ad he cool olygo + ca be obaed fo afe a sees of subdvsos. Hece + s bouded by he covex hull of. Howeve oe ha + ( ) ()d ()d ( + ) +

9 758 L e al. / J Zhejag Uv SCI 25 6A(7): We have l. + Theefoe l l + (9) oe ha () whe (). I hs case we have. Fo he covex hull oey fo ay u [ + ] we ow ha (u) les wh he covex hull of + + fo soe. Togehe wh Eq.(9) we coclude he heoe. Theoe 3 eas ha ecusve subdvso of cool olygo leads o s coesodg AH B-Sle cuve so s o dffcul o ove he V. D. oey ad he covexy esevg oey below: (7) V. D. oey o lae esecs a AH B-Sle cuve oe ofe ha esecs he coesodg cool olygo. Because AH Béze bass s secal AH B-Sle bass we easly ge ha AH Béze cuves have V. D. oey oo. (8) Covexy esevg oey If he cool olygo s covex he he coesodg AH B-Sle cuve s also covex. By he o seg heoe we ca easly ge he oey (9) of he AH Sle: (9) The AH B-Sle bass s B-bass: Poof Ise a o a ad l eeaedly ul he obaed ullces of o ad l ae esecvely ad he old bass ca be exessed by he ew bass. Le us deoe he bass fucos geeaed afe he h o seg o as ( + ( ) ()... ()) s hus he + + l + whee ew bass 2 has edo eolao oey. Fo [Seco 2 of (Maa ad Peña 999) ad Seco 2 of (Maa e al. 2)] we ow ha f a bass has edo eolao oey V. D. oey ao of uy ad covex hull oees s oalzed oally osve so he ew bass 2 s oalzed oally osve. Accodg o he oey of seg a ew o (Theoe ) he asfoao ax bewee + ad s oe-baded ax so he asfoao ax bewee ad 2 ca be decoosed o a oduc of bdagoal facos. Thus we deduce ha he AH B-Sle bass s oalzed oally osve. By he defo of he B-bass we wll show he followg equao holds fo evey j: () + f [ l] j + ( ) j + () (2) If <j ad ++ < j++ le ( j )/2 we have: () + f j ( + ) j + () If ++ j++ le + + he he fe u ode of + s j ode hghe ha fe u ode of j+ so l ( ) / ( ) + j ha s Eq.(2) holds. Whe >j ad > j le ( + )/ 2 we have Eq.(2) holds. Whe >j ad j le + he he fe u ode of + s j ode hghe ha fe u ode of j+ so l ( ) / ( ) ha s Eq.(2) holds. + + j + By Pooso 3.2 (Cace ad Peña 994) ad Seco 3 AH B-Sle bass s oalzed B-bass. Theefoe AH B-Sle bass has oal shae esevg oees ad oal sably oees. AH B-Sle suface Exacly as he cosuco of B-Sle eso oduc sufaces fo B-Sle cuves a AH B-Sle suface ca be cosuced usg eso + oduc. Le U { u } { } + V v j j be wo o sequeces he a AH B-Sle suface wh cool eshes j ca be defed as uv ( ) ( u ) ( v) j j j j

10 L e al. / J Zhejag Uv SCI 25 6A(7): u [ u u ] v [ v v ] l. + l + I whch (u) j (v) ae he AH B-Sle bass fucos wh o sequece U V esecvely. Is oees ca be deduced fo he oees of he AH B-Sle such as he covex hull oey ad he covexy esevg oey. The subdvso foulae ca be used boh decos ec. Refeeces Cace J.M. Peña J.M 994. Toally osve fo shae esevg cuve desg ad oaly of B-Sles. Coue Aded Geoec Desg : Che Q.Y. Wag G.Z. 23. A class of Béze-le cuves. Coue Aded Geoec Desg 2: Koch P.E. Lyche T. 99. Cosuco of Exoeal e- so B-Sles of Abay Ode. I: Laue P.J. Le Méhaué A. Schuae L.L.(Eds.) Cuves ad Sufaces. Acadec Pess ew Yo Lü Y.G. Wag G.Z. Yag X Ufo hyebolc olyoal B-Sle cuves. Coue Aded Geoec Desg 9: Maa E. Peña J.M Coe cug algohs assocaed wh oal shae esevg eeseaos. Coue Aded Geoec Desg 6: Maa E. Peña J.M. Sáchez-Reyes J. 2. Shae esevg aleaves o he aoal Béze odel. Coue Aded Geoec Desg 8:37-6. Peña. J.M Shae Pesevg Reeseaos Coue Aded Geoec Desg. ova Scece Publshes Coac (ew Yo). Wag G.Z. Che Q.Y. Zhou M.H. 24. UAT B-B-Sle cuves. Coue Aded Geoec Desg 2: Welcoe cobuos fo all ove he wold h:// The Joual as o ese he laes develoe ad achevee scefc eseach Cha ad oveseas o he wold's scefc couy; JZUS s eded by a eaoal boad of dsgushed foeg ad Chese scess. Ad a eaoalzed sadad ee evew syse s a esseal ool fo hs Joual's develoe; JZUS has bee acceed by CA E Coedex SA AJ ZM CABI BIOSIS (ZR) IM/MEDLIE CSA (ASF/CE/CIS/Co/EC/EM/ESPM/MD/MTE/O/SSS*/WR) fo absacg ad dexg esecvely sce saed 2; JZUS wll feaue Scece & Egeeg subjecs Vol. A 2 ssues/yea ad Lfe Scece & Boechology subjecs Vol. B 2 ssues/yea; JZUS has lauched hs ew colu Scece Lees ad waly welcoe scess all ove he wold o ublsh he laes eseach oes less ha 3 4 ages. Ad assue he hese Lees o be ublshed abou 3 days; JZUS has led s webse (h:// o CossRef: h:// (do:.63/jzus.25.xxxx); MEDLIE: h:// Hgh- We: h://hghwe.safod.edu/o/jouals.dl; Pceo Uvesy Lbay: h://lbweb5.ceo.edu/ejouals/.

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2 Joh Rley Novembe ANSWERS O ODD NUMBERED EXERCISES IN CHAPER Seo Eese -: asvy (a) Se y ad y z follows fom asvy ha z Ehe z o z We suppose he lae ad seek a oado he z Se y follows by asvy ha z y Bu hs oads

More information

The Stability of High Order Max-Type Difference Equation

The Stability of High Order Max-Type Difference Equation Aled ad Comuaoal Maemacs 6; 5(): 5-55 ://wwwsceceulsggoucom/j/acm do: 648/jacm653 ISSN: 38-565 (P); ISSN: 38-563 (Ole) Te Saly of g Ode Ma-Tye Dffeece Equao a Ca-og * L Lue Ta Xue Scool of Maemacs ad Sascs

More information

On the Quasi-Hyperbolic Kac-Moody Algebra QHA7 (2)

On the Quasi-Hyperbolic Kac-Moody Algebra QHA7 (2) Ieaoal Reeach Joual of Egeeg ad Techology (IRJET) e-issn: 9 - Volume: Iue: May- www.e.e -ISSN: 9-7 O he Qua-Hyebolc Kac-Moody lgeba QH7 () Uma Mahewa., Khave. S Deame of Mahemac Quad-E-Mllah Goveme College

More information

Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Bandung, Bandung, 40132, Indonesia *

Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Bandung, Bandung, 40132, Indonesia * MacWllams Equvalece Theoem fo he Lee Wegh ove Z 4 leams Baa * Fakulas Maemaka da Ilmu Pegeahua lam, Isu Tekolog Badug, Badug, 403, Idoesa * oesodg uho: baa@mahbacd BSTRT Fo codes ove felds, he MacWllams

More information

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse P a g e Vol Issue7Ver,oveber Global Joural of Scece Froer Research Asypoc Behavor of Soluos of olear Delay Dffereal Equaos Wh Ipulse Zhag xog GJSFR Classfcao - F FOR 3 Absrac Ths paper sudes he asypoc

More information

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1 Lecue su Fes of efeece Ivce ude sfoos oo of H wve fuco: d-fucos Eple: e e - µ µ - Agul oeu s oo geeo Eule gles Geec slos cosevo lws d Noehe s heoe C4 Lecue - Lbb Fes of efeece Cosde fe of efeece O whch

More information

CONTROL ROUTH ARRAY AND ITS APPLICATIONS

CONTROL ROUTH ARRAY AND ITS APPLICATIONS 3 Asa Joual of Cool, Vol 5, No, pp 3-4, Mach 3 CONTROL ROUTH ARRAY AND ITS APPLICATIONS Dazha Cheg ad TJTa Bef Pape ABSTRACT I hs pape he Rouh sably ceo [6] has bee developed o cool Rouh aay Soe foulas

More information

( ) ( ) Weibull Distribution: k ti. u u. Suppose t 1, t 2, t n are times to failure of a group of n mechanisms. The likelihood function is

( ) ( ) Weibull Distribution: k ti. u u. Suppose t 1, t 2, t n are times to failure of a group of n mechanisms. The likelihood function is Webll Dsbo: Des Bce Dep of Mechacal & Idsal Egeeg The Uvesy of Iowa pdf: f () exp Sppose, 2, ae mes o fale of a gop of mechasms. The lelhood fco s L ( ;, ) exp exp MLE: Webll 3//2002 page MLE: Webll 3//2002

More information

Suppose we have observed values t 1, t 2, t n of a random variable T.

Suppose we have observed values t 1, t 2, t n of a random variable T. Sppose we have obseved vales, 2, of a adom vaable T. The dsbo of T s ow o belog o a cea ype (e.g., expoeal, omal, ec.) b he veco θ ( θ, θ2, θp ) of ow paamees assocaed wh s ow (whee p s he mbe of ow paamees).

More information

Fault-tolerant Output Feedback Control for a Class of Multiple Input Fuzzy Bilinear Systems

Fault-tolerant Output Feedback Control for a Class of Multiple Input Fuzzy Bilinear Systems Sesos & asduces Vol 7 Issue 6 Jue 04 pp 47-5 Sesos & asduces 04 by IFSA Publshg S L hp://wwwsesospoalco Faul-olea Oupu Feedbac Cool fo a Class of Mulple Ipu Fuzzy Blea Syses * YU Yag WAG We School of Eleccal

More information

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005.

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005. Techc Appedx fo Iveoy geme fo Assemy Sysem wh Poduc o Compoe eus ecox d Zp geme Scece 2005 Lemm µ µ s c Poof If J d µ > µ he ˆ 0 µ µ µ µ µ µ µ µ Sm gumes essh he esu f µ ˆ > µ > µ > µ o K ˆ If J he so

More information

The Solutions of Initial Value Problems for Nonlinear Fourth-Order Impulsive Integro-Differential Equations in Banach Spaces

The Solutions of Initial Value Problems for Nonlinear Fourth-Order Impulsive Integro-Differential Equations in Banach Spaces WSEAS TRANSACTIONS o MATHEMATICS Zhag Lglg Y Jgy Lu Juguo The Soluos of Ial Value Pobles fo Nolea Fouh-Ode Ipulsve Iego-Dffeeal Equaos Baach Spaces Zhag Lglg Y Jgy Lu Juguo Depae of aheacs of Ta Yua Uvesy

More information

ABSOLUTE INDEXED SUMMABILITY FACTOR OF AN INFINITE SERIES USING QUASI-F-POWER INCREASING SEQUENCES

ABSOLUTE INDEXED SUMMABILITY FACTOR OF AN INFINITE SERIES USING QUASI-F-POWER INCREASING SEQUENCES Available olie a h://sciog Egieeig Maheaics Lees 2 (23) No 56-66 ISSN 249-9337 ABSLUE INDEED SUMMABILIY FACR F AN INFINIE SERIES USING QUASI-F-WER INCREASING SEQUENCES SKAIKRAY * RKJAI 2 UKMISRA 3 NCSAH

More information

(1) Cov(, ) E[( E( ))( E( ))]

(1) Cov(, ) E[( E( ))( E( ))] Impac of Auocorrelao o OLS Esmaes ECON 3033/Evas Cosder a smple bvarae me-seres model of he form: y 0 x The four key assumpos abou ε hs model are ) E(ε ) = E[ε x ]=0 ) Var(ε ) =Var(ε x ) = ) Cov(ε, ε )

More information

dm dt = 1 V The number of moles in any volume is M = CV, where C = concentration in M/L V = liters. dcv v

dm dt = 1 V The number of moles in any volume is M = CV, where C = concentration in M/L V = liters. dcv v Mg: Pcess Aalyss: Reac ae s defed as whee eac ae elcy lue M les ( ccea) e. dm he ube f les ay lue s M, whee ccea M/L les. he he eac ae beces f a hgeeus eac, ( ) d Usually s csa aqueus eeal pcesses eac,

More information

ON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT

ON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT V M Chacko E CONVE AND INCREASIN CONVE OAL IME ON ES RANSORM ORDER R&A # 4 9 Vol. Decembe ON OAL IME ON ES RANSORM ORDER V. M. Chacko Depame of Sascs S. homas Collee hss eala-68 Emal: chackovm@mal.com

More information

EMA5001 Lecture 3 Steady State & Nonsteady State Diffusion - Fick s 2 nd Law & Solutions

EMA5001 Lecture 3 Steady State & Nonsteady State Diffusion - Fick s 2 nd Law & Solutions EMA5 Lecue 3 Seady Sae & Noseady Sae ffuso - Fck s d Law & Soluos EMA 5 Physcal Popees of Maeals Zhe heg (6) 3 Noseady Sae ff Fck s d Law Seady-Sae ffuso Seady Sae Seady Sae = Equlbum? No! Smlay: Sae fuco

More information

14. Poisson Processes

14. Poisson Processes 4. Posso Processes I Lecure 4 we roduced Posso arrvals as he lmg behavor of Bomal radom varables. Refer o Posso approxmao of Bomal radom varables. From he dscusso here see 4-6-4-8 Lecure 4 " arrvals occur

More information

SUBSEQUENCE CHARACTERIZAT ION OF UNIFORM STATISTICAL CONVERGENCE OF DOUBLE SEQUENCE

SUBSEQUENCE CHARACTERIZAT ION OF UNIFORM STATISTICAL CONVERGENCE OF DOUBLE SEQUENCE Reseach ad Coucatos atheatcs ad atheatcal ceces Vol 9 Issue 7 Pages 37-5 IN 39-6939 Publshed Ole o Novebe 9 7 7 Jyot cadec Pess htt//yotacadecessog UBEQUENCE CHRCTERIZT ION OF UNIFOR TTITIC CONVERGENCE

More information

are positive, and the pair A, B is controllable. The uncertainty in is introduced to model control failures.

are positive, and the pair A, B is controllable. The uncertainty in is introduced to model control failures. Lectue 4 8. MRAC Desg fo Affe--Cotol MIMO Systes I ths secto, we cosde MRAC desg fo a class of ult-ut-ult-outut (MIMO) olea systes, whose lat dyacs ae lealy aaetezed, the ucetates satsfy the so-called

More information

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations Joural of aheacs ad copuer Scece (4 39-38 Soluo of Ipulsve Dffereal Equaos wh Boudary Codos Ters of Iegral Equaos Arcle hsory: Receved Ocober 3 Acceped February 4 Avalable ole July 4 ohse Rabba Depare

More information

The Poisson Process Properties of the Poisson Process

The Poisson Process Properties of the Poisson Process Posso Processes Summary The Posso Process Properes of he Posso Process Ierarrval mes Memoryless propery ad he resdual lfeme paradox Superposo of Posso processes Radom seleco of Posso Pos Bulk Arrvals ad

More information

- 1 - Processing An Opinion Poll Using Fuzzy Techniques

- 1 - Processing An Opinion Poll Using Fuzzy Techniques - - Pocessg A Oo Poll Usg Fuzzy Techues by Da Peu Vaslu ABSTRACT: I hs ae we deal wh a mul cea akg oblem, based o fuzzy u daa : he uose s o comae he effec of dffee mecs defed o he sace of fuzzy umbes o

More information

Fairing of Parametric Quintic Splines

Fairing of Parametric Quintic Splines ISSN 46-69 Eglad UK Joual of Ifomato ad omputg Scece Vol No 6 pp -8 Fag of Paametc Qutc Sples Yuau Wag Shagha Isttute of Spots Shagha 48 ha School of Mathematcal Scece Fuda Uvesty Shagha 4 ha { P t )}

More information

Generalisation on the Zeros of a Family of Complex Polynomials

Generalisation on the Zeros of a Family of Complex Polynomials Ieol Joul of hemcs esech. ISSN 976-584 Volume 6 Numbe 4. 93-97 Ieol esech Publco House h://www.house.com Geelso o he Zeos of Fmly of Comlex Polyomls Aee sgh Neh d S.K.Shu Deme of hemcs Lgys Uvesy Fdbd-

More information

DUALITY IN MULTIPLE CRITERIA AND MULTIPLE CONSTRAINT LEVELS LINEAR PROGRAMMING WITH FUZZY PARAMETERS

DUALITY IN MULTIPLE CRITERIA AND MULTIPLE CONSTRAINT LEVELS LINEAR PROGRAMMING WITH FUZZY PARAMETERS Ida Joual of Fudameal ad ppled Lfe Sceces ISSN: 223 6345 (Ole) Ope ccess, Ole Ieaoal Joual valable a www.cbech.o/sp.ed/ls/205/0/ls.hm 205 Vol.5 (S), pp. 447-454/Noua e al. Reseach cle DULITY IN MULTIPLE

More information

Exponential Synchronization of the Hopfield Neural Networks with New Chaotic Strange Attractor

Exponential Synchronization of the Hopfield Neural Networks with New Chaotic Strange Attractor ITM Web of Cofeeces, 0509 (07) DOI: 0.05/ mcof/070509 ITA 07 Expoeal Sychozao of he Hopfeld Neual Newos wh New Chaoc Sage Aaco Zha-J GUI, Ka-Hua WANG* Depame of Sofwae Egeeg, Haa College of Sofwae Techology,qogha,

More information

Professor Wei Zhu. 1. Sampling from the Normal Population

Professor Wei Zhu. 1. Sampling from the Normal Population AMS570 Pofesso We Zhu. Samplg fom the Nomal Populato *Example: We wsh to estmate the dstbuto of heghts of adult US male. It s beleved that the heght of adult US male follows a omal dstbuto N(, ) Def. Smple

More information

Continuous Time Markov Chains

Continuous Time Markov Chains Couous me Markov chas have seay sae probably soluos f a oly f hey are ergoc, us lke scree me Markov chas. Fg he seay sae probably vecor for a couous me Markov cha s o more ffcul ha s he scree me case,

More information

Structure and Some Geometric Properties of Nakano Difference Sequence Space

Structure and Some Geometric Properties of Nakano Difference Sequence Space Stuctue ad Soe Geoetic Poeties of Naao Diffeece Sequece Sace N Faied ad AA Baey Deatet of Matheatics, Faculty of Sciece, Ai Shas Uivesity, Caio, Egyt awad_baey@yahooco Abstact: I this ae, we exted the

More information

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction refeed Soluos for R&D o Desg Deermao of oe Equao arameers Soluos for R&D o Desg December 4, 0 refeed orporao Yosho Kumagae refeed Iroduco hyscal propery daa s exremely mpora for performg process desg ad

More information

The Properties of Probability of Normal Chain

The Properties of Probability of Normal Chain I. J. Coep. Mah. Sceces Vol. 8 23 o. 9 433-439 HIKARI Ld www.-hkar.co The Properes of Proaly of Noral Cha L Che School of Maheacs ad Sascs Zheghou Noral Uversy Zheghou Cy Hea Provce 4544 Cha cluu6697@sa.co

More information

On the hydrogen wave function in Momentum-space, Clifford algebra and the Generating function of Gegenbauer polynomial

On the hydrogen wave function in Momentum-space, Clifford algebra and the Generating function of Gegenbauer polynomial O he hoge we fco Moe-sce ffo geb he eeg fco of egebe oo Meh Hge Hss To ce hs eso: Meh Hge Hss O he hoge we fco Moe-sce ffo geb he eeg fco of egebe oo 8 HL I: h- hs://hches-oeesf/h- Sbe o J 8 HL s

More information

The algebraic immunity of a class of correlation immune H Boolean functions

The algebraic immunity of a class of correlation immune H Boolean functions Ieraoal Coferece o Advaced Elecroc Scece ad Techology (AEST 06) The algebrac mmuy of a class of correlao mmue H Boolea fucos a Jgla Huag ad Zhuo Wag School of Elecrcal Egeerg Norhwes Uversy for Naoales

More information

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall 8. Queueg sysems lec8. S-38.45 - Iroduco o Teleraffc Theory - Fall 8. Queueg sysems Coes Refresher: Smle eleraffc model M/M/ server wag laces M/M/ servers wag laces 8. Queueg sysems Smle eleraffc model

More information

MAT 516 Curve and Surface Methods for CAGD [Kaedah Lengkung dan Permukaan untuk RGBK]

MAT 516 Curve and Surface Methods for CAGD [Kaedah Lengkung dan Permukaan untuk RGBK] UNIVERSITI SAINS MALAYSIA Secod Semese Examao / Academc Sesso Jue MAT 56 Cuve ad Suface Mehods fo CAGD [Kaedah Legkug da Pemukaa uuk RGBK] Duao : hous [Masa : am] Please check ha hs examao ae cosss of

More information

International Journal of Mathematics Trends and Technology (IJMTT) Volume 47 Number 1 July 2017

International Journal of Mathematics Trends and Technology (IJMTT) Volume 47 Number 1 July 2017 Iteatioal Joual of Matheatics Teds ad Techology (IJMTT) Volue 47 Nube July 07 Coe Metic Saces, Coe Rectagula Metic Saces ad Coo Fixed Poit Theoes M. Sivastava; S.C. Ghosh Deatet of Matheatics, D.A.V. College

More information

Midterm Exam. Tuesday, September hour, 15 minutes

Midterm Exam. Tuesday, September hour, 15 minutes Ecoomcs of Growh, ECON560 Sa Fracsco Sae Uvers Mchael Bar Fall 203 Mderm Exam Tuesda, Sepember 24 hour, 5 mues Name: Isrucos. Ths s closed boo, closed oes exam. 2. No calculaors of a d are allowed. 3.

More information

χ be any function of X and Y then

χ be any function of X and Y then We have show that whe we ae gve Y g(), the [ ] [ g() ] g() f () Y o all g ()() f d fo dscete case Ths ca be eteded to clude fuctos of ay ube of ado vaables. Fo eaple, suppose ad Y ae.v. wth jot desty fucto,

More information

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters Leas Squares Fg LSQF wh a complcaed fuco Theeampleswehavelookedasofarhavebeelearheparameers ha we have bee rg o deerme e.g. slope, ercep. For he case where he fuco s lear he parameers we ca fd a aalc soluo

More information

Analysis of a Stochastic Lotka-Volterra Competitive System with Distributed Delays

Analysis of a Stochastic Lotka-Volterra Competitive System with Distributed Delays Ieraoal Coferece o Appled Maheac Sulao ad Modellg (AMSM 6) Aaly of a Sochac Loa-Volerra Copeve Sye wh Drbued Delay Xagu Da ad Xaou L School of Maheacal Scece of Togre Uvery Togre 5543 PR Cha Correpodg

More information

Parameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data

Parameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data Avlble ole wwwsceceeccom Physcs Poce 0 475 480 0 Ieol Cofeece o Mecl Physcs Bomecl ee Pmee smo Hyohess es of wo Neve Boml Dsbuo Poulo wh Mss D Zhwe Zho Collee of MhemcsJl Noml UvesyS Ch zhozhwe@6com Absc

More information

Solution to Some Open Problems on E-super Vertex Magic Total Labeling of Graphs

Solution to Some Open Problems on E-super Vertex Magic Total Labeling of Graphs Aalable a hp://paed/aa Appl Appl Mah ISS: 9-9466 Vol 0 Isse (Deceber 0) pp 04- Applcaos ad Appled Maheacs: A Ieraoal Joral (AAM) Solo o Soe Ope Probles o E-sper Verex Magc Toal Labelg o Graphs G Marh MS

More information

ON THE EXTENSION OF WEAK ARMENDARIZ RINGS RELATIVE TO A MONOID

ON THE EXTENSION OF WEAK ARMENDARIZ RINGS RELATIVE TO A MONOID wwweo/voue/vo9iue/ijas_9 9f ON THE EXTENSION OF WEAK AENDAIZ INGS ELATIVE TO A ONOID Eye A & Ayou Eoy Dee of e Nowe No Uvey Lzou 77 C Dee of e Uvey of Kou Ou Su E-: eye76@o; you975@yooo ABSTACT Fo oo we

More information

( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi

( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi Assgmet /MATH 47/Wte Due: Thusday Jauay The poblems to solve ae umbeed [] to [] below Fst some explaatoy otes Fdg a bass of the colum-space of a max ad povg that the colum ak (dmeso of the colum space)

More information

Geometric Modeling

Geometric Modeling Geomerc Modelg 9.58. Crves coed Cc Bezer ad B-Sle Crves Far Chaers 4-5 8 Moreso Chaers 4 5 4 Tycal Tyes of Paramerc Crves Corol os flece crve shae. Ierolag Crve asses hrogh all corol os. Herme Defed y

More information

On Probability Density Function of the Quotient of Generalized Order Statistics from the Weibull Distribution

On Probability Density Function of the Quotient of Generalized Order Statistics from the Weibull Distribution ISSN 684-843 Joua of Sac Voue 5 8 pp. 7-5 O Pobaby Dey Fuco of he Quoe of Geeaed Ode Sac fo he Webu Dbuo Abac The pobaby dey fuco of Muhaad Aee X k Y k Z whee k X ad Y k ae h ad h geeaed ode ac fo Webu

More information

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent oucms Couga Gas Mchal Kazha (6.657) Ifomao abou h Sma (6.757) hav b pos ol: hp://www.cs.hu.u/~msha Tch Spcs: o M o Tusay afoo. o Two paps scuss ach w. o Vos fo w s caa paps u by Thusay vg. Oul Rvw of Sps

More information

Applying p-balanced Energy Technique to Solve Liouville-Type Problems in Calculus

Applying p-balanced Energy Technique to Solve Liouville-Type Problems in Calculus Wold cdey o Scece, Eee d Techoloy Ieol Joul o hecl d ouol Sceces Vol:, No:6, 8 ly -lced Eey Techue o Solve Louvlle-Tye Poles lculus L Wu, Ye L, J Lu Ieol Scece Idex, hecl d ouol Sceces Vol:, No:6, 8 wseo/pulco/95

More information

NUMERICAL EVALUATION of DYNAMIC RESPONSE

NUMERICAL EVALUATION of DYNAMIC RESPONSE NUMERICAL EVALUATION of YNAMIC RESPONSE Aalycal solo of he eqao of oo for a sgle degree of freedo syse s sally o ossble f he excao aled force or grod accelerao ü g -vares arbrarly h e or f he syse s olear.

More information

Strong Result for Level Crossings of Random Polynomials

Strong Result for Level Crossings of Random Polynomials IOSR Joual of haacy ad Biological Scieces (IOSR-JBS) e-issn:78-8, p-issn:19-7676 Volue 11, Issue Ve III (ay - Ju16), 1-18 wwwiosjoualsog Stog Result fo Level Cossigs of Rado olyoials 1 DKisha, AK asigh

More information

A Modeling Method of SISO Discrete-Event Systems in Max Algebra

A Modeling Method of SISO Discrete-Event Systems in Max Algebra A Modelg Mehod of SISO Dscee-Eve Syses Max Algeba Jea-Lous Bood, Laue Hadou, P. Cho To ce hs veso: Jea-Lous Bood, Laue Hadou, P. Cho. A Modelg Mehod of SISO Dscee-Eve Syses Max Algeba. Euopea Cool Cofeece

More information

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002 Mmm lkelhood eme of phylogey BIO 9S/ S 90B/ MH 90B/ S 90B Iodco o Bofomc pl 00 Ovevew of he pobblc ppoch o phylogey o k ee ccodg o he lkelhood d ee whee d e e of eqece d ee by ee wh leve fo he eqece. he

More information

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending CUIC SLINE CURVES Cubc Sples Marx formulao Normalsed cubc sples Alerae ed codos arabolc bledg AML7 CAD LECTURE CUIC SLINE The ame sple comes from he physcal srume sple drafsme use o produce curves A geeral

More information

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3.

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3. C. Trael me cures for mulple reflecors The ray pahs ad rael mes for mulple layers ca be compued usg ray-racg, as demosraed Lab. MATLAB scrp reflec_layers_.m performs smple ray racg. (m) ref(ms) ref(ms)

More information

Brownian Motion and Stochastic Calculus. Brownian Motion and Stochastic Calculus

Brownian Motion and Stochastic Calculus. Brownian Motion and Stochastic Calculus Browa Moo Sochasc Calculus Xogzh Che Uversy of Hawa a Maoa earme of Mahemacs Seember, 8 Absrac Ths oe s abou oob decomoso he bascs of Suare egrable margales Coes oob-meyer ecomoso Suare Iegrable Margales

More information

Strong Result for Level Crossings of Random Polynomials. Dipty Rani Dhal, Dr. P. K. Mishra. Department of Mathematics, CET, BPUT, BBSR, ODISHA, INDIA

Strong Result for Level Crossings of Random Polynomials. Dipty Rani Dhal, Dr. P. K. Mishra. Department of Mathematics, CET, BPUT, BBSR, ODISHA, INDIA Iteatioal Joual of Reseach i Egieeig ad aageet Techology (IJRET) olue Issue July 5 Available at http://wwwijetco/ Stog Result fo Level Cossigs of Rado olyoials Dipty Rai Dhal D K isha Depatet of atheatics

More information

A note on Turán number Tk ( 1, kn, )

A note on Turán number Tk ( 1, kn, ) A oe o Turá umber T (,, ) L A-Pg Beg 00085, P.R. Cha apl000@sa.com Absrac: Turá umber s oe of prmary opcs he combaorcs of fe ses, hs paper, we wll prese a ew upper boud for Turá umber T (,, ). . Iroduco

More information

Shrinkage Estimators for Reliability Function. Mohammad Qabaha

Shrinkage Estimators for Reliability Function. Mohammad Qabaha A - Najah Uv. J. es. (N. Sc.) Vol. 7 3 Shkage Esmaos fo elably Fuco مقدرات التقلص لدالة الفاعلية ohammad Qabaha محمد قبها Depame of ahemacs Faculy of Scece A-Najah Naoal Uvesy alese E-mal: mohqabha@mal.ajah.edu

More information

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( )

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( ) 5-1. We apply Newon s second law (specfcally, Eq. 5-). (a) We fnd he componen of he foce s ( ) ( ) F = ma = ma cos 0.0 = 1.00kg.00m/s cos 0.0 = 1.88N. (b) The y componen of he foce s ( ) ( ) F = ma = ma

More information

Increasing the Image Quality of Atomic Force Microscope by Using Improved Double Tapered Micro Cantilever

Increasing the Image Quality of Atomic Force Microscope by Using Improved Double Tapered Micro Cantilever Rece Reseaces Teecocaos foacs Eecocs a Sga Pocessg ceasg e age Qa of oc Foce Mcope Usg pove oe Tapee Mco aeve Saeg epae of Mecaca Egeeg aava Bac sac za Uves aava Tea a a_saeg@aavaa.ac. sac: Te esoa feqec

More information

Overview. Review Superposition Solution. Review Superposition. Review x and y Swap. Review General Superposition

Overview. Review Superposition Solution. Review Superposition. Review x and y Swap. Review General Superposition ylcal aplace Soltos ebay 6 9 aplace Eqato Soltos ylcal Geoety ay aetto Mechacal Egeeg 5B Sea Egeeg Aalyss ebay 6 9 Ovevew evew last class Speposto soltos tocto to aal cooates Atoal soltos of aplace s eqato

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

Key words: Fractional difference equation, oscillatory solutions,

Key words: Fractional difference equation, oscillatory solutions, OSCILLATION PROPERTIES OF SOLUTIONS OF FRACTIONAL DIFFERENCE EQUATIONS Musafa BAYRAM * ad Ayd SECER * Deparme of Compuer Egeerg, Isabul Gelsm Uversy Deparme of Mahemacal Egeerg, Yldz Techcal Uversy * Correspodg

More information

Spectrum of The Direct Sum of Operators. 1. Introduction

Spectrum of The Direct Sum of Operators. 1. Introduction Specu of The Diec Su of Opeaos by E.OTKUN ÇEVİK ad Z.I.ISMILOV Kaadeiz Techical Uivesiy, Faculy of Scieces, Depae of Maheaics 6080 Tabzo, TURKEY e-ail adess : zaeddi@yahoo.co bsac: I his wok, a coecio

More information

= y and Normed Linear Spaces

= y and Normed Linear Spaces 304-50 LINER SYSTEMS Lectue 8: Solutos to = ad Nomed Lea Spaces 73 Fdg N To fd N, we eed to chaacteze all solutos to = 0 Recall that ow opeatos peseve N, so that = 0 = 0 We ca solve = 0 ecusvel backwads

More information

A Second Kind Chebyshev Polynomial Approach for the Wave Equation Subject to an Integral Conservation Condition

A Second Kind Chebyshev Polynomial Approach for the Wave Equation Subject to an Integral Conservation Condition SSN 76-7659 Eglad K Joural of forao ad Copug Scece Vol 7 No 3 pp 63-7 A Secod Kd Chebyshev olyoal Approach for he Wave Equao Subec o a egral Coservao Codo Soayeh Nea ad Yadollah rdokha Depare of aheacs

More information

FIBONACCI-LIKE SEQUENCE ASSOCIATED WITH K-PELL, K-PELL-LUCAS AND MODIFIED K-PELL SEQUENCES

FIBONACCI-LIKE SEQUENCE ASSOCIATED WITH K-PELL, K-PELL-LUCAS AND MODIFIED K-PELL SEQUENCES Joual of Appled Matheatcs ad Coputatoal Mechacs 7, 6(), 59-7 www.ac.pcz.pl p-issn 99-9965 DOI:.75/jac.7..3 e-issn 353-588 FIBONACCI-LIKE SEQUENCE ASSOCIATED WITH K-PELL, K-PELL-LUCAS AND MODIFIED K-PELL

More information

Lagrangian & Hamiltonian Mechanics:

Lagrangian & Hamiltonian Mechanics: XII AGRANGIAN & HAMITONIAN DYNAMICS Iouco Hamlo aaoal Pcple Geealze Cooaes Geealze Foces agaga s Euao Geealze Momea Foces of Cosa, agage Mulples Hamloa Fucos, Cosevao aws Hamloa Dyamcs: Hamlo s Euaos agaga

More information

Upper Bound For Matrix Operators On Some Sequence Spaces

Upper Bound For Matrix Operators On Some Sequence Spaces Suama Uer Bou formar Oeraors Uer Bou For Mar Oeraors O Some Sequece Saces Suama Dearme of Mahemacs Gaah Maa Uersy Yogyaara 558 INDONESIA Emal: suama@ugmac masomo@yahoocom Isar D alam aer aa susa masalah

More information

Math 7409 Homework 2 Fall from which we can calculate the cycle index of the action of S 5 on pairs of vertices as

Math 7409 Homework 2 Fall from which we can calculate the cycle index of the action of S 5 on pairs of vertices as Math 7409 Hoewok 2 Fall 2010 1. Eueate the equivalece classes of siple gaphs o 5 vetices by usig the patte ivetoy as a guide. The cycle idex of S 5 actig o 5 vetices is 1 x 5 120 1 10 x 3 1 x 2 15 x 1

More information

On EPr Bimatrices II. ON EP BIMATRICES A1 A Hence x. is said to be EP if it satisfies the condition ABx

On EPr Bimatrices II. ON EP BIMATRICES A1 A Hence x. is said to be EP if it satisfies the condition ABx Iteatoal Joual of Mathematcs ad Statstcs Iveto (IJMSI) E-ISSN: 3 4767 P-ISSN: 3-4759 www.jms.og Volume Issue 5 May. 4 PP-44-5 O EP matces.ramesh, N.baas ssocate Pofesso of Mathematcs, ovt. ts College(utoomous),Kumbakoam.

More information

The Non-Truncated Bulk Arrival Queue M x /M/1 with Reneging, Balking, State-Dependent and an Additional Server for Longer Queues

The Non-Truncated Bulk Arrival Queue M x /M/1 with Reneging, Balking, State-Dependent and an Additional Server for Longer Queues Alied Maheaical Sciece Vol. 8 o. 5 747-75 The No-Tucaed Bul Aival Queue M x /M/ wih Reei Bali Sae-Deede ad a Addiioal Seve fo Loe Queue A. A. EL Shebiy aculy of Sciece Meofia Uiveiy Ey elhebiy@yahoo.co

More information

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China,

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China, Mahemacal ad Compuaoal Applcaos Vol. 5 No. 5 pp. 834-839. Assocao for Scefc Research VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS Hoglag Lu Aguo Xao Yogxag Zhao School of Mahemacs

More information

Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies

Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies Ecologcal Moogahs, 84, 04,. 45 67 Ó 04 by he Ecologcal ocey of Aeca Raefaco ad exaolao wh Hll ubes: a faewo fo salg ad esao seces dvesy sudes ANNE CHAO,,6 NICHOLA J. GOELLI,. C. HIEH, ELIZABEH L. ANDER,

More information

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA QR facorzao Ay x real marx ca be wre as AQR, where Q s orhogoal ad R s upper ragular. To oba Q ad R, we use he Householder rasformao as follows: Le P, P, P -, be marces such ha P P... PPA ( R s upper ragular.

More information

Chapter 3: Maximum-Likelihood & Bayesian Parameter Estimation (part 1)

Chapter 3: Maximum-Likelihood & Bayesian Parameter Estimation (part 1) Aoucemes Reags o E-reserves Proec roosal ue oay Parameer Esmao Bomercs CSE 9-a Lecure 6 CSE9a Fall 6 CSE9a Fall 6 Paer Classfcao Chaer 3: Mamum-Lelhoo & Bayesa Parameer Esmao ar All maerals hese sles were

More information

Chapter 3: Vectors and Two-Dimensional Motion

Chapter 3: Vectors and Two-Dimensional Motion Chape 3: Vecos and Two-Dmensonal Moon Vecos: magnude and decon Negae o a eco: eese s decon Mulplng o ddng a eco b a scala Vecos n he same decon (eaed lke numbes) Geneal Veco Addon: Tangle mehod o addon

More information

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables Joural of Sceces Islamc epublc of Ira 6(: 63-67 (005 Uvers of ehra ISSN 06-04 hp://scecesuacr Some Probabl Iequales for Quadrac Forms of Negavel Depede Subgaussa adom Varables M Am A ozorga ad H Zare 3

More information

XII. Addition of many identical spins

XII. Addition of many identical spins XII. Addto of may detcal sps XII.. ymmetc goup ymmetc goup s the goup of all possble pemutatos of obects. I total! elemets cludg detty opeato. Each pemutato s a poduct of a ceta fte umbe of pawse taspostos.

More information

-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL

-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL UPB Sc B See A Vo 72 I 3 2 ISSN 223-727 MUTIPE -HYBRID APACE TRANSORM AND APPICATIONS TO MUTIDIMENSIONA HYBRID SYSTEMS PART II: DETERMININ THE ORIINA Ve PREPEIŢĂ Te VASIACHE 2 Ace co copeeă oă - pce he

More information

Cyclically Interval Total Colorings of Cycles and Middle Graphs of Cycles

Cyclically Interval Total Colorings of Cycles and Middle Graphs of Cycles Ope Joural of Dsree Mahemas 2017 7 200-217 hp://wwwsrporg/joural/ojdm ISSN Ole: 2161-7643 ISSN Pr: 2161-7635 Cylally Ierval Toal Colorgs of Cyles Mddle Graphs of Cyles Yogqag Zhao 1 Shju Su 2 1 Shool of

More information

Mathematical Formulation

Mathematical Formulation Mahemacal Formulao The purpose of a fe fferece equao s o appromae he paral ffereal equao (PE) whle maag he physcal meag. Eample PE: p c k FEs are usually formulae by Taylor Seres Epaso abou a po a eglecg

More information

Modeling and simulation of through-focus images for dimensional analysis of nanoscale structures

Modeling and simulation of through-focus images for dimensional analysis of nanoscale structures Modelg ad sulao of hough-focus ages fo desoal aalyss of aoscale sucues Xuguo CHEN a hyua LIU * b Chuawe ZHAN a Yua MA b ad Jlog ZHU b a Wuha Naoal Laboaoy fo Ooelecocs Huazhog Uvesy of cece ad Techology

More information

GENERALIZATION OF AN IDENTITY INVOLVING THE GENERALIZED FIBONACCI NUMBERS AND ITS APPLICATIONS

GENERALIZATION OF AN IDENTITY INVOLVING THE GENERALIZED FIBONACCI NUMBERS AND ITS APPLICATIONS #A39 INTEGERS 9 (009), 497-513 GENERALIZATION OF AN IDENTITY INVOLVING THE GENERALIZED FIBONACCI NUMBERS AND ITS APPLICATIONS Mohaad Faokh D. G. Depatent of Matheatcs, Fedows Unvesty of Mashhad, Mashhad,

More information

such that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1

such that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1 Scholas Joual of Egeeg ad Techology (SJET) Sch. J. Eg. Tech. 0; (C):669-67 Scholas Academc ad Scetfc Publshe (A Iteatoal Publshe fo Academc ad Scetfc Resouces) www.saspublshe.com ISSN -X (Ole) ISSN 7-9

More information

FORCED VIBRATION of MDOF SYSTEMS

FORCED VIBRATION of MDOF SYSTEMS FORCED VIBRAION of DOF SSES he respose of a N DOF sysem s govered by he marx equao of moo: ] u C] u K] u 1 h al codos u u0 ad u u 0. hs marx equao of moo represes a sysem of N smulaeous equaos u ad s me

More information

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF EDA/DIT6 Real-Tme Sysems, Chalmers/GU, 0/0 ecure # Updaed February, 0 Real-Tme Sysems Specfcao Problem: Assume a sysem wh asks accordg o he fgure below The mg properes of he asks are gve he able Ivesgae

More information

The MacWilliams Identity of the Linear Codes over the Ring F p +uf p +vf p +uvf p

The MacWilliams Identity of the Linear Codes over the Ring F p +uf p +vf p +uvf p Reearch Joural of Aled Scece Eeer ad Techoloy (6): 28-282 22 ISSN: 2-6 Maxwell Scefc Orazao 22 Submed: March 26 22 Acceed: Arl 22 Publhed: Auu 5 22 The MacWllam Idey of he Lear ode over he R F +uf +vf

More information

LIPSCHITZ ESTIMATES FOR MULTILINEAR COMMUTATOR OF MARCINKIEWICZ OPERATOR

LIPSCHITZ ESTIMATES FOR MULTILINEAR COMMUTATOR OF MARCINKIEWICZ OPERATOR Reseh d ouiios i heis d hei Siees Vo. Issue Pges -46 ISSN 9-699 Puished Oie o Deee 7 Joi Adei Pess h://oideiess.e IPSHITZ ESTIATES FOR UTIINEAR OUTATOR OF ARINKIEWIZ OPERATOR DAZHAO HEN Dee o Siee d Ioio

More information

African Journal of Science and Technology (AJST) Science and Engineering Series Vol. 4, No. 2, pp GENERALISED DELETION DESIGNS

African Journal of Science and Technology (AJST) Science and Engineering Series Vol. 4, No. 2, pp GENERALISED DELETION DESIGNS Af Joul of See Tehology (AJST) See Egeeg See Vol. 4, No.,. 7-79 GENERALISED DELETION DESIGNS Mhel Ku Gh Joh Wylff Ohbo Dee of Mhe, Uvey of Nob, P. O. Bo 3097, Nob, Key ABSTRACT:- I h e yel gle ele fol

More information

APPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS

APPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS Joa of Aed Mahema ad Comaoa Meha 4 3( 6-73 APPLCATON OF A Z-TRANSFORMS METHOD FOR NVESTGATON OF MARKOV G-NETWORKS Mha Maay Vo Nameo e of Mahema Ceohowa Uey of Tehoogy Cęohowa Poad Fay of Mahema ad Come

More information

The Nehari Manifold for a Class of Elliptic Equations of P-laplacian Type. S. Khademloo and H. Mohammadnia. afrouzi

The Nehari Manifold for a Class of Elliptic Equations of P-laplacian Type. S. Khademloo and H. Mohammadnia. afrouzi Wold Alied cieces Joal (8): 898-95 IN 88-495 IDOI Pblicaios = h x g x x = x N i W whee is a eal aamee is a boded domai wih smooh boday i R N 3 ad< < INTRODUCTION Whee s ha is s = I his ae we ove he exisece

More information

A GENERAL CLASS OF ESTIMATORS UNDER MULTI PHASE SAMPLING

A GENERAL CLASS OF ESTIMATORS UNDER MULTI PHASE SAMPLING TATITIC IN TRANITION-ew sees Octobe 9 83 TATITIC IN TRANITION-ew sees Octobe 9 Vol. No. pp. 83 9 A GENERAL CLA OF ETIMATOR UNDER MULTI PHAE AMPLING M.. Ahed & Atsu.. Dovlo ABTRACT Ths pape deves the geeal

More information

ÖRNEK 1: THE LINEAR IMPULSE-MOMENTUM RELATION Calculate the linear momentum of a particle of mass m=10 kg which has a. kg m s

ÖRNEK 1: THE LINEAR IMPULSE-MOMENTUM RELATION Calculate the linear momentum of a particle of mass m=10 kg which has a. kg m s MÜHENDİSLİK MEKANİĞİ. HAFTA İMPULS- MMENTUM-ÇARPIŞMA Linea oenu of a paicle: The sybol L denoes he linea oenu and is defined as he ass ies he elociy of a paicle. L ÖRNEK : THE LINEAR IMPULSE-MMENTUM RELATIN

More information

Support Appendix The Logistics Impact of a Mixture of Order-Streams in a Manufacturer-Retailer System Ananth V Iyer and Apurva Jain

Support Appendix The Logistics Impact of a Mixture of Order-Streams in a Manufacturer-Retailer System Ananth V Iyer and Apurva Jain So Aedx Te og Ia o a Mxe o Ode-Sea a Maae-Reale Sye Aa V Iye ad Ava Ja Teoe 4: e ad q be e obably geeag o o e eady-ae be o ode ee e ye by a avg H ode ad a M ode eevely Te ad q Wee ad be e ee oo o e ollowg

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

Leader-Following Consensus of Nonlinear Multi-Agent Systems Based on Parameterized Lyapunov Function

Leader-Following Consensus of Nonlinear Multi-Agent Systems Based on Parameterized Lyapunov Function ODRES JOURL OF ELECRICL EGIEERIG VOL 5 O 2 SUER 25 3 Leade-Followg Cosesus of olea ul-ge Sysems Based o Paameezed Lyauov Fuco Pegah aba Saad 2 ohammad ehd ada okha Shasadegh Behouz Safaeada bsac hs ae

More information

7 Wave Equation in Higher Dimensions

7 Wave Equation in Higher Dimensions 7 Wave Equaion in Highe Dimensions We now conside he iniial-value poblem fo he wave equaion in n dimensions, u c u x R n u(x, φ(x u (x, ψ(x whee u n i u x i x i. (7. 7. Mehod of Spheical Means Ref: Evans,

More information

NONDIFFERENTIABLE MATHEMATICAL PROGRAMS. OPTIMALITY AND HIGHER-ORDER DUALITY RESULTS

NONDIFFERENTIABLE MATHEMATICAL PROGRAMS. OPTIMALITY AND HIGHER-ORDER DUALITY RESULTS HE PUBLISHING HOUSE PROCEEDINGS OF HE ROMANIAN ACADEMY, See A, OF HE ROMANIAN ACADEMY Volue 9, Nube 3/8,. NONDIFFERENIABLE MAHEMAICAL PROGRAMS. OPIMALIY AND HIGHER-ORDER DUALIY RESULS Vale PREDA Uvety

More information