DS-CDMA Cellular Systems Performance with Base Station Assignment, Power Control Error, and Beamforming over Multipath Fading

Size: px
Start display at page:

Download "DS-CDMA Cellular Systems Performance with Base Station Assignment, Power Control Error, and Beamforming over Multipath Fading"

Transcription

1 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 DS-CDMA Ceuar Syses Perforae wh Base Sao Assge Power Coro Error ad Beaforg over Mupah Fadg Mohaad Dosaraa Moghada Hadreza Bahsh ad Ghoareza Dadashzadeh Depare of Eera Egeerg sa Azad Uversy Qazv Brah Qazv ra _doghada@au.a.r Depare of Eera Egeerg Shahed Uversy ehra ra ahsh@shahed.a.r gdadashzadeh@shahed.a.r Asra he erferee reduo apay of aea arrays ase sao assge ad he power oro agorhs have ee osdered separaey as eas o rease he apay wreess ouao ewors. hs paper we propose ase sao assge ehod ased o zg he raser power BSA-MP ehue a dre seuee-ode dvso upe aess DS-CDMA reever he presee of freuey-seeve Rayegh fadg ad power oro error PCE. hs reever osss of osraed eas ea suared CMS agorh ahed fer MF ad axa rao og MRC hree sages. Aso we prese swhed-ea SB ehue he frs sage of he RAKE reever for ehag sga o erferee pus ose rao SNR DS-CDMA euar syses. he suao resus dae ha BSA-MP ehue a sgfay prove he ewor error rae BER oparso wh he oveoa ase. Fay we dsuss o hree paraeers of he PCE uer of resovae pahs ad hae propagao odos pah-oss expoe ad shadowg ad her effes o apay of he syse va soe opuer suaos. KEYWORDS Adapve eaforg ase sao assge DS-CDMA power oro error ahed fer axa rao og. NRODUCON Syses uzg ode-dvso upe aess CDMA are urrey eg depoyed aroud he oury ad aroud he word respose o he ever reasg dead for euar/persoa ouaos serves. Exesve researh has ee pushed o he perforae aayss of CDMA syses. Fadg s aog he aor faors affeg he perforae of suh syses. Fadg s geeray haraerzed aordg o s effe over a geographa area. arge-sae fadg osss of pah oss ad shadowg he aer er referrg o fuuaos he reeved sga ea power. arge-sae fadg s affeed y proe erra oours ewee he raser ad reever. Sa-sae fadg s he oo referee o he rapd hages sga apude ad phase over a sa spaa separao. hs wor he oed effe of arge- ad sa-sae fadg are osdered. he sa-sae fadg s assued o e govered y he Rayegh dsruo Rayegh fadg [] []. Besdes fadg CDMA syses are susepe o he ear-far proe. s we ow ha order o fuy expo he poea advaage of CDMA syses power oro s reured o ouera he effes of he ear-far proe. he CDMA syse apay s axzed f eah DO : 0.5/

2 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 oe raser power eve s oroed so ha s sga arrves a he ase sao BS wh he u reured sga o erferee pus ose rao SNR []-[7]. However whe appyg power oro prae he perforae s resred y a uer of aos ad herefore perfe power oro ao e aheved. he ssue of he effe of power oro errors o CDMA syses has reeved a grea dea of aeo over he as few years []-[4]. Aordgy hs paper we osder he effe of power oro error PCE o dre-seuee DS-CDMA euar syses. Aso dversy s oe effeve ehue for ehag he SNR for wreess ewors. Dversy expos he rado aure of rado propagao y fdg depede or a eas hghy uorreaed sga pahs for ouao. f oe rado pah udergoes a deep fade aoher depede pah ay have a srog sga. By havg ore ha oe pah o see fro he SNR a he reever a e proved. he dversy shee a e dvded o hree ehods: he spae dversy; he e dversy; 3 he freuey dversy. hese shees he sae forao s frs reeved or rased a dffere oaos or e sos/freuey ads. Afer ha hese sgas are oed o rease he reeved SNR. he aea array s a exape of he spae dversy whh uses a eaforer o rease he SNR for a paruar dreo [8]-[0]. hs wor we use osraed eas ea suared CMS agorh ad swhed-ea SB ehue for he spae dversy. o prove he perforae of euar syses ase sao assge BSA ehue a e used. he ase sao assge a uer of ase saos are poea reevers of a oe raser. Here he oeve s o deere he assge of users o ase saos whh zes he aoaed oe powers []-[4]. spe ode ad upe-e syses he user s oeed o he eares ase sao. hs way s o opa euar syses uder he shadowg ad upah fadg haes ad a rease he syse BER. hs paper we prese ase sao assge ehod ased o zg he raser power BSA-MP for dereasg he BER a es [5]-[7]. he goa of hs paper s o exed he wors [5]-[9] y osderg o upe-e syse BSA-MP ehue ad PCE. [5]-[7] we proposed he BSA-MP ehue DS-CDMA syses upah fadg haes whou osderg he PCE. Aso [8] ad [9] a RAKE reever sge-e syse was proposed he presee of freuey-seeve Rayegh fadg hae ad he oveoa BSA was osdered. hs wor he perforae aayss of DS-CDMA syse freuey-seeve Rayegh fadg hae has ee suded. f he deay spread a upah hae s arger ha a frao of a syo he deayed opoes w ause er-syo erferee S. Adapve reever eaforg shees have ee wdey used o redue oh o-hae erferee CC ad S ad o derease he error rae BER y adusg he ea paer suh ha he effeve SNR a he oupu of he eaforer s opay reased [0]. hs paper a RAKE reever DS-CDMA syse s aayzed hree sages aordg o Fgure [8]. he frs sage hs reever uses CMS adapve eaforg agorh o fd opu aea weghs assug perfe esao of he hae paraeers dreo deay ad power for he desred user. he desred user resovae pahs dreos are fed o he eaforer o redue he er-pah erferee P fro oher dreos. Aso he RAKE reever uses oveoa deoduao he seod sage ad oveoa axa rao og MRC he hrd sage o redue upe aess erferee MA ad he oher erferees. Redug he MA ad CC w furher derease he syse BER. he orgazao of he reader of hs paper s as foows. he syse ode s gve Seo. he RAKE reever sruure s desred Seo 3. Seo 4 we propose he BSA-MP ehue. Seo 5 we prese he SB ehue. Fay suao resus ad ousos are gve Seo 6 ad Seo 7 respevey. 86

3 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 Fgure. Bo dagra of a hree-sage RAKE reever DS-CDMA syse [8]. SYSEM MODE hs paper we fous o he up ouao pahs a DS-CDMA euar syse. he hae s odeed as a freuey seeve hae wh Rayegh dsruo ad ogora dsrued shadowg. ay we osder pahs for eah ha opay oed hrough a RAKE reever aordg o Fg.. Aso we assue ha here are M ave ase saos he ewor wh K users oeed o h ase sao. A eah ase sao a aea array of S sesors ad N weghs s epoyed where S = N o reeve sgas fro a users. Aso for spy we assue a syhroous DS-CDMA shee ad BPSK oduao order o spfy he aayss of proposed ehue. Addoay hs paper we assue a sow fadg hae he hae rado paraeers do o hage sgfay durg he erva. Hee he reeved sga he ase sao ad sesor s fro a users a e wre as [] [8] [] r s = Pλ Γ x y α = exp π sd sθ / λ where P = E / represes he reeved sga power of a users wh e he presee of perfe power oro where E ad are he eergy per ad perod for a users respevey. he varae λ s PCE for user e user whh s assued o foow a og-ora dsruo ad hus a e wre as λ = 0 where υ s a υ /0 σ υ for a users [4]. Aso ; Gaussa rado varae wh ea 0 ad varae s he pseudo ose PN hps of user wh a hp perod of s he forao seuee of user wh a perod of = G where G s proessg ga; s he h pah e deay for user ; θ s he dreo of arrva DoA he h pah for user ; α s he opex Gaussa fadg hae oeffe fro he h pah of user ; λ s sga waveegh; d s he dsae ewee he aea eees ha for avod he spaa aasg shoud e defed as d = 0.5λ ; s a addve whe Gaussa ose AWGN proess wh a wo-sded power spera desy PSD of N 0 /. Aso for Γ x y s defed as oveoa BSA ehue 87

4 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 Fgure. he dsae ewee wo pars of oe rasers ad ase sao reevers [] Γ ξ { 0 } /0 α x y = d x y Θ α d x y 0 ξ /0 ; S ; S where are he dsae ewee user ad BS ad BS respevey see Fgure ; Aso he varae Θ defed he se of he eares BSs o user ; ξ s a rado varae odeg he shadowg ewee user ad α s pah-oss expoe; d x y ad d x y BS ; S BS s he se of users ha oeed o BS ad oeed o BS [4]. BS o S o s he se of users ha o Aso shoud e eoed ha he rased power of user e o BS he ase of he PPC s gve y ξ x y /0 0 P p = d α 3 Aordgy he reeved sga he ase sao sesor s for user s gve y [8] = Pλ α exp π sd sθ λ r s / s = where where s he erferee for user sesor s ad a e show o e s s M K = Pλ Γ x y = exp α = = 5 π sd sθ / λ K s he uer of users e ad M s he uer of ase saos/es. 3. RAKE RECEVER PERFORMANCE ANAYSS he RAKE reever sruure he DS-CDMA syse s show Fgure. he reeved sga s spaay proessed y a eaforg ru wh CMS agorh oe for eah resovae pah eaforers. he resua sga s he passed o o a se of parae 4 88

5 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 ahed fers MFs o a fger-y-fger ass. Aso he oupu sgas fro he ahed fers are oed aordg o he oveoa MRC prpe ad he are fed o he deso ru of he desred user. 3.. Cosraed MS Agorh s we ow ha a array of N weghs has N degree of freedo for adapve eaforg [8] []. hs eas ha wh a array of N weghs oe a geeraes N paer us ad a ea axu desred dreos. Fro E. 5 s ear ha he M uer of users s K u = K ad he uer of erferee sgas s K u. o u a = of hese erferee sgas; oe woud have o have K u weghs whh s o praa. So we fous oy o he pahs of he desred user. hus he u uer of he aea array weghs s where ypay vares fro o 6 [8]. hs paper we use he CMS adapve eaforg agorh. hs agorh s a grade ased agorh o ze he oa proessor oupu power ased o he oo dreo osra. he adapve agorh s desged o adap effey agreee wh he evroe ad ae o peraey preserve he desred freuey respose he oo dreo whe zg he oupu power of he array. he oed for of he osra s aed osra for arrowad eaforg [0] []. hs for osder a arrowad eaforer where he arrowad sga fro eah eee of sar aea are uped y he opex wegh auaed y usg arrowad adapve eaforg agorh ad he sued o produe he oupu of he array. he defo of he opex weghs of hs eaforer he h erao for user he h pah s as foows [] [3]. [ ] = w w w 0... N w 6 Aordgy he oupu of he array he h erao he h pah for user where [ ] r 0 r r N y H w r s gve y = 7 r =.... he expeed oupu power of he array he h erao s gve y where. r. E y * H H = w r r w = E y y E = w H R w r r E s deoed he expeao ad R r r s he orreao arx of he reeved veor A rea-e CMS agorh for deerg he opa wegh veor for user pah s [] [3]: w w H = w µ g w a θ = 8 he h 9 where 89

6 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 θ = exp sθ... exp N s ] [ d d θ a 0 deoes spaa respose of he array for user he h pah. Aso E. 9 w s he ew wegh opued a he h erao for user he h pah. Aso he varae saar µ deoes a posve saar grade sep sze ha oros he overgee haraers of he agorh ha s how fas ad how ose he esaed weghs approah he opa weghs ad g H surfae R w r r w w deoes a uased esae of he grade of he power whh s he expeed oupu power of he array wh respe o w afer he h erao. he agorh s osraed eause he wegh veor H θ = sasfes he osra a eah erao ha s w a agorh as foows []. where θ. Rewre he CMS g a w = β w µ w N β θ a θ H he grade of w R wh respe o g r r w H a = N w s gve y = R H w R w w * r r r r w = w 3 ad s opuao usg hs expresso reures owedge of R r r whh oray s o avaae prae. For a sadard MS agorh a esae of he grade a eah erao s ade y repag sa eadg o r r R y s ose sape r H r avaae a e = r y * g w 4 he CMS s a fas overgee agorh. However s drasay sesve o he sah he dreo of arrva. Meawhe he weghs esaed y he sadard agorh are sesve o he sga power reurg a ower sep sze he presee of a srog sga for he agorh o overge whh ur regardg he derease of s-aduse error he overgee e s reased [] [4]. shoud e eoed ha for he aea arrays wegh veor he CMS agorh ad for g µ w overge afer a few erao s approxaey eua o he uer of eaforer weghs.e. = N [4]. Aordgy he oupu sga fro he h eaforer =... a e wre as [8] y where = P α ~ λ 5 s a zero ea Gaussa ose of varae ~ σ ad he P s defed as 90

7 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 9 g P ~ α θ λ = = 6 ad he MA s defed as M K g y x P α θ λ Γ = = = = 7 where θ g s he agude respose of he h eaforer for user oward he DoA θ. 3.. Mahed Fer Sage Usg eaforg he frs sage w redue he P for he desred user ad he MA fro he oher users whose sgas arrve a dffere ages fro he desred user sga ou-ea erferee. Now he seod sage of he RAKE reever he oupu sga fro he h eaforer s drey passes o o a fer ahed o he desred user s sgaure seuee. he h ahed fer oupu orrespodg o he h s [8]: P z ~ = α λ 8 where d ~ ~ = 9 d = 0 ad d = f we assue ha he pahs deays fro a users are ess ha he syo durao < for a users sgas o a pahs he h P ad MA a he oupu of he h ahed fer are expressed as R g P ~ α θ λ = = ad

8 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 K M = Pλ Γ x y g θ α R = = = where he auoorreao fuo R s [] [8]: 3 R = d 4 f a users deays are upes of he hp perod he where he auoorreao fuo G G R = G = 0= 0 R 5 R s: R = he ase of a axa-egh seuee -seuee ad for 0 we have []: d 6 R = / G / G ; ; Maxa Rao Cog Sage Dversy og has ee osdered as a effe way o oa upah fadg eause he oed SNR s reased opared wh he SNR of eah dversy rah. he opu oer s he MRC whose SNR s he su of he SNR s of eah dvdua dversy rah [] [5]. Afer he fger-ahed fer he fgers sgas are oed aordg o he MRC prpe he hrd sage of he RAKE reever. hs paper we use he oveoa MRC ha he sga of user he h pah s oed usg upyg y he opex ougae ofα. he SNR oupu of he RAKE reever for user [5] odoed oα s gve as [8] where SNR SNR = SNR α α 8 = Pα e α = 9 E ~ E E βυ s he SNR oupu of he RAKE reever pah for user ad β = 0 / 0. 9

9 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 O he oher had E[ λ ] for a users a e wre as [6] E β συ / [ λ ] e = 30 Now usg Es. 9- ad 30 we a e rewre he SNR E. 9 as foows [7] [8]. where η = M K SNR βυ α e α = 3 β σ / 0.5 η e υ E / N x y α g θ R = = = α Γ = g θ R 0 3 Γ ad α = E α. Aso E. 3 x y = E Γ x y order o perfor he BER we assue Gaussa approxao for he proay desy fuo of erferee pus ose. he odoa BER for a BPSK oduao s [] [8]: where α α BER = Q SNR 33 x = exp u / Q du π x HE BSA-MP ECHNQUE he syse apay gh e proved f he users are aowed o swh o aerave ase saos espeay whe here are ogesed areas he ewor. Ovousy whe up perforae s of oer he swhg shoud happe ased o he oa erferees see y he ase saos [4]. So far we have osdered he power oro proe for a uer of raser-reever pars wh fxed assges whh a e used up or dow oe ouao syses. a up searo where ase saos are eupped wh aea arrays he proe of o power oro ad eaforg as we as ase sao assge auray arses []. hs paper we odfy he BSA-MP ehue upah fadg hae o suppor ase sao assge as we. he odfed ehue a e suarzed as foows [5]-[7]. ay y he oveoa BSA ehue eah oe oes o s ase sao aordg o E.. Esae he wegh veor for a users wh he CMS agorh usg E.. 93

10 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 Fgure eas eah ase sao wh he SB ehue Fgure 4. See of ea for wo users wo pahs wh he SB ehue 3 Cauae he rased power of a users usg E Fay Kr = Ku / M users ha her rased power s hgher ha he oher users o e rasferred o oher ase saos aordg o he foowg euao where he fuo x reurs he eger poro of a uer x. where Γ x y Θ = d Θ d α ξ { d x y 0 } /0 ξ /0 α x y 0 α ξ { d x y 0 } /0 α x y 0 ξ /0 ; S ; S ; S BS BS S BS s he se of users ha are e u o oeed o BS [4]. shoud e eoed ha he ehue for users ha are prese he order of es he BER a e effevey redued. 5. HE SWCHED-BEAM ECHNQUE Oe spe aerave o he fuy adapve aea s he swhed-ea arheure whh he es ea s hose fro a uer of fxed seered eas. Swhed-ea syses are ehoogay he spes ad a e peeed y usg a uer of fxed depede or dreoa aeas [9]. We s he odos of he SB ehue for hs paper as foows [30]. Aordg o Fgure 3 eas overage age s o s 0. hus eah ase sao has 36 eas. o 35 o 30 ad overap ewee oseuve eas Aordg o Fgure 4 eah user a e use oe ea for s eah pah o ouae wh a ase sao a ay e. 94

11 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 Fgure 5. oao po of ase saos ad users four es 6 Fgure 6. a Foa feeda geeraor for FSR poyoa g D D D = for sxsage shf regser Expadg he oa ery 03 o ary for [] 6. SMUAON RESUS We osder M = 4 ase saos for a four-e CDMA syse o a grd ad sze as Fgure 5. We assue a ufor ear array of S o-dreoa aeas eah ase sao wh aea spag d = λ /. Aso we assue he pu daa rae = 9.6 Kps ; he uer of aea weghs N = 3 ; freuey-seeve fadg hae wh = resovae propagao pahs; varae of he opex Gaussa fadg hae oeffe σ α = 4dB ; pah-oss opoe α = 4 ; varae of he og-ora shadow fadg σ ξ = 8dB ; resouo R = ; a vaue for wegh veors he CMS agorh w 0 = 0. aso s assued ha he dsruo of users a es s ufor. hs paper we use -seuee geeraor wh proessg ga G = 64 ased o ear feeda shf regser FSR ru usg he Foa feeda approah []. hs sruure s show Fgure 6 a. Aso aordg o [] we use he seuee geeraed y he poyoa orrespodg o he ery he oa represeao of geeraor poyoa ORGP= [03]* for a sx-sage shf regser. Fgure 6 shows expadg he oa ery 03 o ary g D = D D. for. he he FSR poyoa s 6 Fgure 7 shows he average BER versus he sga o ose rao SNR for dffere reevers oe wo ad hree-sage reevers K = 3 ave users ad a og-oray dsrued PCE u whσ υ = 4dB. shoud e eoed ha hs suao K = 8 users a e rasferred o r 95

12 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 oher ase saos wh he BSA-MP ehue. s ear ha MF oy reever oe-sage reever ad he ase of he oveoa BSA ehue we s have he error foor a hgh SNR. Usg CMS ad MRC reever wo-sage RAKE reever or CMS MF ad MRC reever he hree-sage RAKE reever as Fgure has a eer perforae ha usg MF oy. Aso we oserve ha usg he BSA-MP ehue CMS MF ad MRC reever he average BER s ower ha he oveoa BSA ehue. For exape a a SNR of 0dB he average BER s for he hree-sage RAKE reever wh he oveoa BSA Fgure 7. Average BER of a users versus he SNR for σ υ = 4dB ad K = 3 u Fgure 8. Average BER of a users versus he SNR for dffere vaues of ehue whe for he BSA-MP ehue he average BER s Aso a e see ha he average BER he CMS agorh s hgher ha he SB ehue. addo we oserve ha usg he BSA-MP ehue SB MF ad MRC reever he average BER s ower ha oher ases. For exape a a SNR of db he average BER usg he BSA-MP ehue s for SB ehue whe he average BER for CMS agorh s Aso s ear ha he MA s o reoved oay ad he perforae s s worse ha he sge user per e oud. Resus for he average BER versus he SNR for CMS MF ad MRC reever ad K u = 3 ave users ad dffere vaues of σ υ are provded Fgure 8. hs fgure sar o Fgure 7 we oserve ha he average BER for he BSA-MP ehue s σ υ 96

13 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 ower ha he oveoa BSA ehue. Aso a e see ha he average BER for σ = 0dB υ perfe power oro s ower ha he oher ases [5]. For exape a a SNR of 0dBad for he BSA-MP ehue he average BER s forσ = 0dB whe for σ υ = db adσ υ = 8dB he average BER are ad 0.0 respevey. Fgure 9 shows he average BER versus he uer of ave users K for dffere reevers as Fgure 7 ad forsnr = 0dB adσ υ = 4dB. A a BER of 0.0 CMS MF ad MRC reever wh he BSA-MP ehue suppor K = 36 users whe for he oveoa BSA u u υ Fgure 9. Average BER versus K u for σ υ = 4dB ad SNR = 0dB Fgure 0. Average BER of a users versus K u for dffere vaues of σ υ ehue suppor Ku = users. addo he fgure shows ha he average BER he CMS agorh s hgher ha he SB ehue. For exape A a BER of ad for he BSA-MP ehue SB MF ad MRC reever suppor Ku = 40 users whe CMS MF ad MRC reever suppor K u = 8 users respevey. Aso a e see ha he hree-sage RAKE reever a aheve ower BER ha he oher reevers. shoud e eoed ha 97

14 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 reasg he uer of ave users K u w rease he uer of users ha a e rasferred o oher ase saos K he BSA-MP ehue. r Fgure 0 preses he average BER versus he uer of ave users as Fgure 8 for SNR = 0dB ad dffere vaues of σ. Sar o Fgure 8 we oserve ha he average BER υ for σ = 0 υ db s ower haσ υ = 48dB. For exape a a BER of 0.0 ad for he BSA- MP ehue he hree-sage RAKE reever whσ υ = 0dBsuppor Ku = 44 users whe for σ υ = 48dB suppor Ku = ad 30 users respevey. Aordgy hs ase wh σ υ fro o 8 db he syse apay degrades fro 9% o 3% opared o he ase of perfe power oro. Fgure. fuee of pah-oss expoe o average BER σ υ = 4 db SNR = 0dB Fgure. fuee of varae of shadowg o average BER σ υ = 4dB SNR = 0dB Oher resus dspayed Fgures ad show he fuee of hae propagao odos pah-oss expoe ad varae of shadowg σ o he average BER for he α CMS MF ad MRC reever ad he BSA-MP ehue. hs suaos we assue SNR = 0dB adσ = 4dB. Fgure we a oserve ha as expeed a rease he υ ξ 98

15 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 pah-oss expoe eas a derease he MA eve ad herefore a provee syse perforae. For exape a a BER of 0.0 apay s respevey 6 36 users for 3 ad 5. Fgure s see ha f σ reases fro 6 o 8 db he uer of ave users ξ dereases y approxaey 55% for a reured average BER of whereas f reases fro 4 o 6 db he apay dereases y approxaey 3%. Fay Fgure 3 shows urves of he average BER versus he uer of ave users forσ υ = 4dB SNR = 0dB ad dffere vaues of he uer of propagao pahs. a e see ha for BER=0.003 he uer of users aowed he syse reases fro 8 o 35 whe vares fro o 4. α = σ ξ Fgure 3. Average BER for dffere vaues of he uer of propagao pahs σ υ = 4dB SNR = 0dB 7. CONCUSONS hs paper we suded he RAKE reever perforae of upe-e DS-CDMA syse wh he spae dversy proessg Rayegh freuey-seeve hae ode power oro error ad ase sao assge. hs reever osss of hree sages. he frs sage wh he CMS agorh he desred users sga a arrary pah s passed ad he P s redued oher pahs eah RAKE fger. Aso hs sage he MA fro oher users s redued. hus he MF a e used for he MA reduo eah RAKE fger he seod sage. Aso he hrd sage he oupu sgas fro he ahed fers are oed aordg o he oveoa MRC prpe ad he are fed o he deso ru for he desred user. Aordgy we proposed BSA-MP ehue o redue he CC ad he MA DS-CDMA euar syses. has ee show ha y usg aea arrays a he ase saos he proposed ehue w derease he average BER of he syse o suppor a sgfay arger uer of users. has aso ee oserved ha he average BER hree-sage RAKE reever s ess ha he oe- ad wo-sage RAKE reevers. O he oher had has ee show ha he average BER he SB ehue s ower ha he CMS agorh. Aso our suaos show ha he varaos power eve due o PCE have a derea effe o syse perforae. 99

16 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 ACKNOWEDGEMEN hs researh was suppored y he sa Azad Uversy Qazv Brah Qazv ra. REFERENCES [] R.. Peerso R. E. Zeer ad D. E. Borh Spread-Speru Couaos. Pree-Ha 995. [] W. Ye ad A. M. Haovh Perforae of euar CDMA wh e se aea array Rayegh fadg ad power oro error EEE rasaos o Couaos vo. 48 o. 7 pp Juy 000. [3] A. Arardo ad D. Sea O he aaya evauao of osed-oop power-oro error sass DS-CDMA euar syses EEE rasaos o Vehuar ehoogy vo. 49 o. 6 pp Nov [4]. Carraso ad G. Feeas Reverse perforae of a DS-CDMA syse wh oh fas ad sow power oroed users EEE rasaos o Wreess Couaos vo. 7 o. 4 pp Apr [5]. Qa ad Z. Ga Varae zao sohas power oro CDMA syse EEE rasaos o Wreess Couaos vo. 5 o. pp Ja [6] M. Raa H. Kovo ad. Haro Adapve osed-oop power oro agorhs for CDMA euar ouao syses EEE rasaos o Vehuar ehoogy vo. 53 o. 6 pp Nov [7] J. Wag ad A. Yu Ope-oop power oro error euar CDMA overay syses EEE Joura o Seeed Areas Couaos vo. 9 o. 7 pp Juy 00. [8] J.. Wag Adsso oro wh dsrued o dversy ad power oro for wreess ewors EEE rasaos o Vehuar ehoogy vo. 58 o. pp Ja [9] K. Kuaa J. MDoough B. Rauh D. Kaow P. N. Garer ad W. Beaforg wh a axu egeropy rero EEE rasaos o Audo Speeh ad aguage Proessg vo. 7 o. 5 pp Juy 009. [0] J. Chag. assuas ad F. Rashd-Farroh Jo raser reever dversy for effe spae dvso uaess EEE rasaos o Wreess Couaos vo. o. pp. 6-7 Ja. 00. [] F. Rashd-Farroh. assuas ad K. J. Ray-u Jo opa power oro ad eaforg wreess ewors usg aea arrays EEE rasaos o Couaos vo. 46 o. 0 pp O [] R. D. Yaes ad C. Huag egraed power oro ad ase sao assge EEE rasaos o Vehuar ehoogy vo. 44 o. 3 pp Aug [3] S. V. Hay A agorh for oed e-se seeo ad power oro o axze euar spread speru apay EEE Joura o Seeed Areas Couaos vo. 3 o. 7 pp Sep [4] M. Mahoud ad E. S. Sousa Jo power oro ase sao assge ad seorzao for CDMA euar syses Pro. 000 EEE Vehuar ehoogy Coferee Boso MA vo. pp Sep [5] M. Dosaraa-Moghada H. Bahsh ad G. Dadashzadeh erferee aagee for DS-CDMA reever hrough ase sao assge upah fadg haes Pro. 00 EEE eraoa Coferee o Wreess Couaos Neworg ad forao Seury Beg Cha pp Jue 00. [6] M. Dosaraa-Moghada H. Bahsh ad G. Dadashzadeh Jo osraed MS agorh ad ase sao assge for DS-CDMA reever upah fadg haes Aeped for 00

17 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 puao he EEE Wreess Couaos Neworg ad Moe Copug Chegdu Cha Sep [7] M. Dosaraa-Moghada H. Bahsh ad G. Dadashzadeh erferee aagee for DS-CDMA syses hrough osed-oop power oro ase sao assge ad eaforg Joura of Wreess Sesor Newor vo. o. 6 pp Jue 00. [8] N. A. Mohaed ad J. G. Duha A ow-opexy oed aea array ad erferee aeao DS-CDMA reever upah fadg haes EEE Joura o Seeed Areas Couaos vo. 0 o. pp Fe. 00. [9] N. A. Mohaed ad J. G. Duha Adapve eaforg for DS-CDMA usg ougae grade agorh a upah fadg hae Pro. 999 EEE Eergg ehooges Syp. Daas X pp Apr [0] F. Rashd-Farroh K. J. Ray-u ad. assuas ras eaforg ad power oro for euar syses EEE Joura o Seeed Areas Couaos vo. 6 o. 8 pp O [] J. va ad. Kwo-Yeug Dga Beaforg Wreess Couaos. Areh-House 996. [] S. Xyu. Xaohua ad Z. Jaag Rous adapve eaforg ased o axu ehood esao eraoa Coferee o Mrowave ad Meer Wave ehoogy vo. 3 pp Apr [3] M. Z. Shar ad. S. Durra Narrowad eaforg agorh for sar aeas eraoa Bhura Coferee o Apped Sees & ehoogy pp Ja [4] S. Hay Adapve fer heory. 3 h ed. New Jersey: Pree Ha 996. [5] N. Kog ad. B. Mse Average SNR of a geerazed dversy seeo og shee EEE Couaos eers vo. 3 o. 3 pp Mar [6] J. M. Roero-Jerez C. eez-aao ad A. Daz-Esrea Effe of power oro perfeos o he reverse of euar CDMA ewors uder upah fadg EEE rasaos o Vehuar ehoogy vo. 53 o. pp. 6-7 Ja [7] J. C. er ad. S. Rappapor Sar Aeas for Wreess Couaos S -95 ad hrd Geerao CDMA Appaos. Pree-Ha 999. [8] M. Dosaraa-Moghada H. Bahsh G. Dadashzadeh ad M. Godarzvad-Cheg Jo ase sao assge power oro error ad adapve eaforg for DS-CDMA euar syses upah fadg haes Aeped for puao EEE Goa Moe Cogress Shagha Cha O [9] B. Ae ad M. Beah O he aayss of swhed-ea aeas for he W-CDMA dow EEE rasaos o Vehuar ehoogy vo. 53 o. 3 pp May 004. [30] M. Dosaraa-Moghada H. Bahsh ad G. Dadashzadeh Jo erazed power oro ad e seorg for erferee aagee CDMA euar syses a D ura evroe Joura of Wreess Sesor Newor vo. o. 8 pp Aug. 00. Auhors Mohaad Dosaraa Moghada was or ehra ra o May He reeved he B.S. degree eera egeerg fro sa Azad Uversy Qazv Brah Qazv ra ad he M.S. degree ouao egeerg fro Ferdows Uversy Mashad ra 00 ad 005 respevey. He s urrey worg oward he Ph.D degree he Depare of Eera Egeerg sa Azad Uversy See & Researh Brah ehra ra. Hs researh eress ude power oro wreess ouaos array ad sasa sga proessg sar aeas ad adapve ferg. 0

18 eraoa Joura of Copuer Newors & Couaos JCNC Vo.3 No. Jauary 0 Hadreza Bahsh was or ehra ra o Apr He reeved he B.S. degree eera egeerg fro ehra Uversy ra 99 he M.S. ad Ph.D. degree Eera Egeerg fro ara Modarres Uversy ra 995 ad 00 respevey. Se 00 he has ee as a Asssa Professor of Eera Egeerg a Shahed Uversy ehra ra. Hs researh eress ude wreess ouaos uuser deeo ad sar aeas. Ghoareza Dadashzadeh was or Ura ra 964. He reeved he B.S. degree ouao egeerg fro Shraz Uversy Shraz ra 99 ad M.S. ad Ph.D. degree ouao egeerg fro ara Modarres Uversy MU ehra ra 996 ad 00 respevey. Fro 998 o 003 he has wored as head researher of Sar Aea for Moe Couao Syses SAMCS ad WAN 80. proe rado ouaos group of ra eeo Researh Ceer RC. Fro 004 o 008 he was dea of Couaos ehoogy sue C RC. He s urrey as Asssae Professor he Depare of Eera Egeerg a Shahed Uversy ehra ra. He s a eer of EEE sue of Eeros forao ad Couao Egeers ECE of Japa ad raa Assoao of Eera ad Eeros Egeers AEEE of ra. He hoored reeved he frs degree of aoa researher 007 fro ra s sry of C. Hs researh eress ude aea desg ad sar aeas. 0

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits.

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits. ose ad Varably Homewor # (8), aswers Q: Power spera of some smple oses A Posso ose A Posso ose () s a sequee of dela-fuo pulses, eah ourrg depedely, a some rae r (More formally, s a sum of pulses of wdh

More information

Chapter 1 - Free Vibration of Multi-Degree-of-Freedom Systems - I

Chapter 1 - Free Vibration of Multi-Degree-of-Freedom Systems - I CEE49b Chaper - Free Vbrao of M-Degree-of-Freedo Syses - I Free Udaped Vbrao The basc ype of respose of -degree-of-freedo syses s free daped vbrao Aaogos o sge degree of freedo syses he aayss of free vbrao

More information

On Metric Dimension of Two Constructed Families from Antiprism Graph

On Metric Dimension of Two Constructed Families from Antiprism Graph Mah S Le 2, No, -7 203) Mahemaal Sees Leers A Ieraoal Joural @ 203 NSP Naural Sees Publhg Cor O Mer Dmeso of Two Cosrued Famles from Aprm Graph M Al,2, G Al,2 ad M T Rahm 2 Cere for Mahemaal Imagg Tehques

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

Collocation Method for Nonlinear Volterra-Fredholm Integral Equations

Collocation Method for Nonlinear Volterra-Fredholm Integral Equations Ope Joural of Appled Sees 5- do:436/oapps6 Publshed Ole Jue (hp://wwwsrporg/oural/oapps) Colloao Mehod for olear Volerra-Fredhol Iegral Equaos Jafar Ahad Shal Parvz Daraa Al Asgar Jodayree Akbarfa Depare

More information

Ensemble Of Image Segmentation With Generalized Entropy Based Fuzzy Clustering

Ensemble Of Image Segmentation With Generalized Entropy Based Fuzzy Clustering Ieraoal Joural of Copuer ad Iforao Tehology (ISSN: 79 0764) Volue 03 Issue 05, Sepeber 014 Eseble Of Iage Segeao Wh Geeralzed Eropy Based Fuzzy Cluserg Ka L *, Zhx Guo Hebe Uversy College of Maheas ad

More information

Proceedings of the 9th UK Conference on Boundary Integral Methods, University of Aberdeen, UK, 8-9th July 2013

Proceedings of the 9th UK Conference on Boundary Integral Methods, University of Aberdeen, UK, 8-9th July 2013 Proeedgs of he 9h U Coferee o Bodar Iegra Mehods Uvers of Aberdee U 8-9h J 03 -D ELASTODYNAMIC PROBLEM FOR AN INTERFACE CRAC UNDER AN OBLIQUE HARMONIC LOADING V. MIUCA ad O. MENSHYOV Cere for Mro- ad Naoehas

More information

RAKE Receiver with Adaptive Interference Cancellers for a DS-CDMA System in Multipath Fading Channels

RAKE Receiver with Adaptive Interference Cancellers for a DS-CDMA System in Multipath Fading Channels AKE v wh Apv f Cs fo DS-CDMA Ss Muph Fg Chs JooHu Y Su M EEE JHog M EEE Shoo of E Egg Sou o Uvs Sh-og Gw-gu Sou 5-74 Ko E-: ohu@su As hs pp pv AKE v wh vs og s popos fo DS-CDMA ss uph fg hs h popos pv

More information

ASYMPTOTIC BEHAVIOR OF SOLUTIONS OF DISCRETE EQUATIONS ON DISCRETE REAL TIME SCALES

ASYMPTOTIC BEHAVIOR OF SOLUTIONS OF DISCRETE EQUATIONS ON DISCRETE REAL TIME SCALES ASYPTOTI BEHAVIOR OF SOLUTIONS OF DISRETE EQUATIONS ON DISRETE REAL TIE SALES J. Dlí B. Válvíová 2 Bro Uversy of Tehology Bro zeh Repul 2 Deprme of heml Alyss d Appled hems Fuly of See Uversy of Zl Žl

More information

Linear Minimum Variance Unbiased Estimation of Individual and Population slopes in the presence of Informative Right Censoring

Linear Minimum Variance Unbiased Estimation of Individual and Population slopes in the presence of Informative Right Censoring Ieraoal Joural of Scefc ad Research Pulcaos Volue 4 Issue Ocoer 4 ISSN 5-353 Lear Mu Varace Uased Esao of Idvdual ad Populao slopes he presece of Iforave Rgh Cesorg VswaahaN * RavaaR ** * Depare of Sascs

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

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

( ) BER PERFORMANCE OF A TH-UWB SYSTEM IN DIFFERENT SCENARIOS USING FAST SIMULATOR INTRODUCTION SYSTEM AND SIGNAL MODEL. Signal description

( ) BER PERFORMANCE OF A TH-UWB SYSTEM IN DIFFERENT SCENARIOS USING FAST SIMULATOR INTRODUCTION SYSTEM AND SIGNAL MODEL. Signal description SIEZ 4 Iege ye Ipa o Iere o Bue ave Serba a Wore Ua Ierea a poovae u Srb veu oi:.538/sieza-4-853-857 PERFORMCE OF H-UWB SYSEM I DIFFERE SCERIOS USIG FS SIMUOR Mara Maraovć J. M. Paez Borrao Sguu Uvery

More information

Fracture analysis of cracked thermopiezoelectric materials by BEM

Fracture analysis of cracked thermopiezoelectric materials by BEM Q. H. Q / Eero Joura o ouar Eee Vo. No.. 83-3 3 Fraure aa o rae heroeoeer aera E Q-Hua Q Deare o eha a Uver a 37 P.R. Cha E-a: Qh@u.eu. ra he ouar eee oruao or aa rae heroeoeer aera ue o hera a eeroea

More information

Fuzzy Possibility Clustering Algorithm Based on Complete Mahalanobis Distances

Fuzzy Possibility Clustering Algorithm Based on Complete Mahalanobis Distances Ieraoal Joural of Sef Egeerg ad See Volue Issue. 38-43 7. ISSN (Ole): 456-736 Fuzzy Possbly Cluserg Algorh Based o Colee ahalaobs Dsaes Sue-Fe Huag Deare of Dgal Gae ad Aao Desg Tae Uvey of are Tehology

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

Learning of Graphical Models Parameter Estimation and Structure Learning

Learning of Graphical Models Parameter Estimation and Structure Learning Learg of Grahal Models Parameer Esmao ad Sruure Learg e Fukumzu he Isue of Sasal Mahemas Comuaoal Mehodology Sasal Iferee II Work wh Grahal Models Deermg sruure Sruure gve by modelg d e.g. Mxure model

More information

An Improvement on Disc Separation of the Schur Complement and Bounds for Determinants of Diagonally Dominant Matrices

An Improvement on Disc Separation of the Schur Complement and Bounds for Determinants of Diagonally Dominant Matrices ISSN 746-7659, Egd, UK Jor of Iformo d Compg See Vo. 5, No. 3, 2, pp. 224-232 A Improveme o Ds Sepro of he Shr Compeme d Bods for Deerms of Dgoy Dom Mres Zhohog Hg, Tgzh Hg Shoo of Mhem Sees, Uversy of

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

ONE APPROACH FOR THE OPTIMIZATION OF ESTIMATES CALCULATING ALGORITHMS A.A. Dokukin

ONE APPROACH FOR THE OPTIMIZATION OF ESTIMATES CALCULATING ALGORITHMS A.A. Dokukin Iero Jor "Iforo Theore & co" Vo 463 ONE PPROH FOR THE OPTIIZTION OF ETITE UTING GORITH Do rc: I h rce he ew roch for ozo of eo ccg gorh ggeed I c e ed for fdg he correc gorh of coexy he coex of gerc roch

More information

ELEC 6041 LECTURE NOTES WEEK 3 Dr. Amir G. Aghdam Concordia University

ELEC 6041 LECTURE NOTES WEEK 3 Dr. Amir G. Aghdam Concordia University ecre Noe Prepared b r G. ghda EE 64 ETUE NTE WEE r. r G. ghda ocorda Uer eceraled orol e - Whe corol heor appled o a e ha co of geographcall eparaed copoe or a e cog of a large ber of p-op ao ofe dered

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

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

PARAMETER IDENTIFICATION-BASED DAMAGE DETECTION FOR LINEAR TIME-VARYING SYSTEMS

PARAMETER IDENTIFICATION-BASED DAMAGE DETECTION FOR LINEAR TIME-VARYING SYSTEMS RMETER IDENTIFICTION-BSED DMGE DETECTION FOR INER TIME-VRING SSTEMS Z.. S Cvl ad Sruural Egeerg Depare, Hog Kog ole Uvers (a prese) Hog Kog College of erospae Egeerg, Nag Uvers of eroaus ad sroaus eople

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

A Mean- maximum Deviation Portfolio Optimization Model

A Mean- maximum Deviation Portfolio Optimization Model A Mea- mamum Devato Portfolo Optmzato Model Wu Jwe Shool of Eoom ad Maagemet, South Cha Normal Uversty Guagzhou 56, Cha Tel: 86-8-99-6 E-mal: wujwe@9om Abstrat The essay maes a thorough ad systemat study

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

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

Sherzod M. Mirakhmedov,

Sherzod M. Mirakhmedov, Approxao by ora dsrbuo for a sape su sapg whou repacee fro a fe popuao Ibrah B Mohaed Uversy of Maaya Maaysa ohaed@ueduy Sherzod M Mrahedov Isue of Maheacs Tashe shrahedov@yahooco Absrac A su of observaos

More information

ESTABILIZATION TIME FOR SUBCRITICAL SYSTEM WITH DIFFERENT EXTERNAL NEUTRON SOURCE

ESTABILIZATION TIME FOR SUBCRITICAL SYSTEM WITH DIFFERENT EXTERNAL NEUTRON SOURCE 03 Iero Nuer Coferee - INC 03 Refe PE Brz Noveer 4-9 03 OCIÇÃO BRILEIR E ENERGI NUCLER - BEN IBN: 978-85-994-05- ETBILIZTION TIE FOR UBCRITICL YTE WITH IFFERENT EXTERNL NEUTRON OURCE Bry. Fose Ferdo C.

More information

A Theoretical Framework for Selecting the Cost Function for Source Routing

A Theoretical Framework for Selecting the Cost Function for Source Routing A Theoreal Framework for Seleg he Cos Fuo for Soure Roug Gag Cheg ad Nrwa Asar Seor ember IEEE Absra Fdg a feasble pah sube o mulple osras a ework s a NP-omplee problem ad has bee exesvely suded ay proposed

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

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

Multi-Period Portfolio Selection with No-Shorting Constraints: Duality Analysis

Multi-Period Portfolio Selection with No-Shorting Constraints: Duality Analysis Joura of Maheaca Face 7 7 75-768 hp://wwwscrporg/oura/f ISSN Oe: 6-44 ISSN Pr: 6-434 Mu-Perod Porfoo Seeco wh No-Shorg Cosras: Duay Aayss Ju Q La Y Maagee Schoo Ja Uversy Guagzhou Cha How o ce hs paper:

More information

Representation of Solutions of Linear Homogeneous Caputo Fractional Differential Equations with Continuous Variable Coefficients

Representation of Solutions of Linear Homogeneous Caputo Fractional Differential Equations with Continuous Variable Coefficients Repor Nuber: KSU MATH 3 E R 6 Represeo o Souos o Ler Hoogeeous puo Fro ere Equos w ouous Vrbe oees Su-Ae PAK Mog-H KM d Hog-o O * Fu o Mes K Sug Uvers Pogg P R Kore * orrespodg uor e: oogo@ooo Absr We

More information

Laplace Transform. Definition of Laplace Transform: f(t) that satisfies The Laplace transform of f(t) is defined as.

Laplace Transform. Definition of Laplace Transform: f(t) that satisfies The Laplace transform of f(t) is defined as. Lplce Trfor The Lplce Trfor oe of he hecl ool for olvg ordry ler dfferel equo. - The hoogeeou equo d he prculr Iegrl re olved oe opero. - The Lplce rfor cover he ODE o lgerc eq. σ j ple do. I he pole o

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

14.3 Frequency-nonselective, slowly fading channel Frequency-nonselective, slowly fading channel. Ideal performance under AWGN

14.3 Frequency-nonselective, slowly fading channel Frequency-nonselective, slowly fading channel. Ideal performance under AWGN CUCM --- Po-g Che --- 43 Fequey-oeeve owy adg hae Oevao o Fo he gue o aheve a PO eve o 4 he ye u povde a SR hghe ha 35dB whh o o paa So aeave ouo houd e ae o opeae he adg ee uh a he ue o eduday e dvey

More information

4.1 Schrödinger Equation in Spherical Coordinates

4.1 Schrödinger Equation in Spherical Coordinates Phs 34 Quu Mehs D 9 9 Mo./ Wed./ Thus /3 F./4 Mo., /7 Tues. / Wed., /9 F., /3 4.. -. Shodge Sphe: Sepo & gu (Q9.) 4..-.3 Shodge Sphe: gu & d(q9.) Copuo: Sphe Shodge s 4. Hdoge o (Q9.) 4.3 gu Moeu 4.4.-.

More information

FROM THE BCS EQUATIONS TO THE ANISOTROPIC SUPERCONDUCTIVITY EQUATIONS. Luis A. PérezP. Chumin Wang

FROM THE BCS EQUATIONS TO THE ANISOTROPIC SUPERCONDUCTIVITY EQUATIONS. Luis A. PérezP. Chumin Wang FROM THE BCS EQUATIONS TO THE ANISOTROPIC SUPERCONDUCTIVITY EQUATIONS J. Samuel Mllá Faulad de Igeería Uversdad Auóoma del Carme Méxo. M Lus A. PérezP Isuo de Físa F UNAM MéxoM xo. Chum Wag Isuo de Ivesgaoes

More information

International Journal of Scientific & Engineering Research, Volume 3, Issue 10, October ISSN

International Journal of Scientific & Engineering Research, Volume 3, Issue 10, October ISSN Ieraoal Joural of cefc & Egeerg Research, Volue, Issue 0, Ocober-0 The eady-ae oluo Of eral hael Wh Feedback Ad Reegg oeced Wh o-eral Queug Processes Wh Reegg Ad Balkg ayabr gh* ad Dr a gh** *Assoc Prof

More information

Approximation of Controllable Set by Semidefinite Programming for Open-Loop Unstable Systems with Input Saturation

Approximation of Controllable Set by Semidefinite Programming for Open-Loop Unstable Systems with Input Saturation Egeerg eers 7:4 E_7_4_ Approxao of Corollable Se by Sedefe Prograg for Ope-oop Usable Syses wh Ipu Saurao Abraha W.. Wag Meber IAENG ad Ye-Mg Che Absra I order o es he effey of sedefe prograg (SDP we apply

More information

Optimal Neuro-controller Synthesis for Impulse-Driven System

Optimal Neuro-controller Synthesis for Impulse-Driven System Opal Neuro-oroller Syhess or Ipulse-Drve Syse Xaohua Wag ad S N Balarsha, Meber, IEEE Absra hs paper preses a ew oroller desg ehque or syses drve wh pulse pus Neessary odos or opal pulse orol are derved

More information

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9 OH BOY! O h Boy!, was or igin a lly cr eat ed in F r en ch an d was a m a jor s u cc ess on t h e Fr en ch st a ge f or young au di enc es. It h a s b een s een by ap pr ox i ma t ely 175,000 sp ect at

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

Probabilistic Graphical Models

Probabilistic Graphical Models Pros Grh Moes 0708 Lerg Coeey Oserve Uree Grh Moes Er Xg Leure O 9 005 Reg: MJCh. 990 Re: or Bs I we ssue he reers or eh CPD re goy eee oes re uy oserve he he kehoo uo eooses o su o o ers oe er oe: D D

More information

4. THE DENSITY MATRIX

4. THE DENSITY MATRIX 4. THE DENSTY MATRX The desy marx or desy operaor s a alerae represeao of he sae of a quaum sysem for whch we have prevously used he wavefuco. Alhough descrbg a quaum sysem wh he desy marx s equvale o

More information

Input-to-state stability of switched nonlinear systems

Input-to-state stability of switched nonlinear systems Scece Cha Seres F: Iforao Sceces 28 SCIENCE IN CHINA PRESS Sprer www.sccha.co fo.sccha.co www.sprerk.co Ipu-o-sae saby of swched oear syses FENG We,2 & ZHANG JFe 2 Coee of Iforao Sceces ad Eeer, Shado

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

Reliability Analysis of Sparsely Connected Consecutive-k Systems: GERT Approach

Reliability Analysis of Sparsely Connected Consecutive-k Systems: GERT Approach Relably Aalyss of Sparsely Coece Cosecuve- Sysems: GERT Approach Pooa Moha RMSI Pv. L Noa-2131 poalovely@yahoo.com Mau Agarwal Deparme of Operaoal Research Uversy of Delh Delh-117, Ia Agarwal_maulaa@yahoo.com

More information

Cyclone. Anti-cyclone

Cyclone. Anti-cyclone Adveco Cycloe A-cycloe Lorez (963) Low dmesoal aracors. Uclear f hey are a good aalogy o he rue clmae sysem, bu hey have some appealg characerscs. Dscusso Is he al codo balaced? Is here a al adjusme

More information

Chebyshev Polynomials for Solving a Class of Singular Integral Equations

Chebyshev Polynomials for Solving a Class of Singular Integral Equations Appled Mahemas, 4, 5, 75-764 Publshed Ole Marh 4 SRes. hp://www.srp.org/joural/am hp://d.do.org/.46/am.4.547 Chebyshev Polyomals for Solvg a Class of Sgular Iegral Equaos Samah M. Dardery, Mohamed M. Alla

More information

Design and Optimization for Energy-Efficient Cooperative MIMO Transmission in Ad Hoc Networks

Design and Optimization for Energy-Efficient Cooperative MIMO Transmission in Ad Hoc Networks Ths arle has bee aeped for publao a fuure ssue of hs joural, bu has o bee fully eded. Coe may hage pror o fal publao. Cao formao: DOI 0.09/TVT.06.536803, IEEE Trasaos o Vehular Tehology Desg ad Opmzao

More information

Hyperbolic Heat Equation as Mathematical Model for Steel Quenching of L-shape and T-shape Samples, Direct and Inverse Problems

Hyperbolic Heat Equation as Mathematical Model for Steel Quenching of L-shape and T-shape Samples, Direct and Inverse Problems SEAS RANSACIONS o HEA MASS RANSER Bos M Be As Bs Hpeo He Eo s Me Moe o See Qe o L-spe -spe Spes De Iese Poes ABIA BOBINSKA o Pss Mes es o L Ze See 8 L R LAIA e@o MARARIA BIKE ANDRIS BIKIS Ise o Mes Cope

More information

Section 3. Measurement Errors

Section 3. Measurement Errors eto 3 Measuremet Errors Egeerg Measuremets 3 Types of Errors Itrs errors develops durg the data aqusto proess. Extrs errors foud durg data trasfer ad storage ad are due to the orrupto of the sgal y ose.

More information

CALIBRATION OF CONSTANT ANGULAR ERROR FOR CBERS-2 IMAGERY WITH FEW GROUND CONTROL POINTS

CALIBRATION OF CONSTANT ANGULAR ERROR FOR CBERS-2 IMAGERY WITH FEW GROUND CONTROL POINTS CALIBRATION OF CONTANT ANGULAR ERROR FOR CBER- IAGER WITH FEW GROUND CONTROL OINT Jupeg U a, * uxao UAN a hel WU a a hool of Reoe esg ad Iforao Egeerg, Wuha Uversy, Wuha, Cha 4379 sregh71@16.o Cosso I,

More information

Turbo Coded MIMO Multiplexing with Iterative Adaptive Soft Parallel Interference Cancellation

Turbo Coded MIMO Multiplexing with Iterative Adaptive Soft Parallel Interference Cancellation Turbo Coe MIMO Mulplexg wh Ierave Aapve Sof Parallel Ierferece Cacellao Akor akaja, eepshkha Garg, a Fuyuk Aach ep. of Elecrcal a Coucaos Egeerg Tohoku Uversy, Sea, Japa akaja@oble.ece.ohoku.ac.jp Absrac

More information

THE LOWELL LEDGER, INDEPENDENT NOT NEUTRAL.

THE LOWELL LEDGER, INDEPENDENT NOT NEUTRAL. E OE EDGER DEEDE O EUR FO X O 2 E RUO OE G DY OVEER 0 90 O E E GE ER E ( - & q \ G 6 Y R OY F EEER F YOU q --- Y D OVER D Y? V F F E F O V F D EYR DE OED UDER EDOOR OUE RER (E EYEV G G R R R :; - 90 R

More information

P a g e 3 6 of R e p o r t P B 4 / 0 9

P a g e 3 6 of R e p o r t P B 4 / 0 9 P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J

More information

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions:

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions: Paramerc coug process models Cosder coug processes: N,,..., ha cou he occurreces of a eve of eres for dvduals Iesy processes: Lelhood λ ( ;,,..., N { } λ < Log-lelhood: l( log L( Score fucos: U ( l( log

More information

Spectral Simulation of Turbulence. and Tracking of Small Particles

Spectral Simulation of Turbulence. and Tracking of Small Particles Specra Siuaio of Turbuece ad Trackig of Sa Parices Hoogeeous Turbuece Saisica ie average properies RMS veociy fucuaios dissipaio rae are idepede of posiio. Hoogeeous urbuece ca be odeed wih radoy sirred

More information

EE 6885 Statistical Pattern Recognition

EE 6885 Statistical Pattern Recognition EE 6885 Sascal Paer Recogo Fall 005 Prof. Shh-Fu Chag hp://www.ee.columba.edu/~sfchag Lecure 5 (9//05 4- Readg Model Parameer Esmao ML Esmao, Chap. 3. Mure of Gaussa ad EM Referece Boo, HTF Chap. 8.5 Teboo,

More information

AC 2-3 AC 1-1 AC 1-2 CO2 AC 1-3 T CO2 CO2 F ES S I O N RY WO M No.

AC 2-3 AC 1-1 AC 1-2 CO2 AC 1-3 T CO2 CO2 F ES S I O N RY WO M No. SHEE OES. OVE PCE HOSS SSOCE PPUCES. VE EW CORO WR. S SE EEVO S EXS. 2. EW SSORS CCOS. S SE EEVO S HOSS. C 2-3 C - C -2 C 2- C -3 C 4- C 2-2 P SUB pproved Filename: :\\2669 RP Performing rts Center HVC\6-C\s\2669-3.dwg

More information

National Conference on Recent Trends in Synthesis and Characterization of Futuristic Material in Science for the Development of Society

National Conference on Recent Trends in Synthesis and Characterization of Futuristic Material in Science for the Development of Society ABSTRACT Naoa Coferece o Rece Tred Syhe ad Characerzao of Fuurc Maera Scece for he Deveome of Socey (NCRDAMDS-208) I aocao wh Ieraoa Joura of Scefc Reearch Scece ad Techoogy Some New Iegra Reao of I- Fuco

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

Reliability Equivalence of a Parallel System with Non-Identical Components

Reliability Equivalence of a Parallel System with Non-Identical Components Ieraoa Mahemaca Forum 3 8 o. 34 693-7 Reaby Equvaece of a Parae Syem wh No-Ideca ompoe M. Moaer ad mmar M. Sarha Deparme of Sac & O.R. oege of Scece Kg Saud Uvery P.O.ox 455 Ryadh 45 Saud raba aarha@yahoo.com

More information

X-Ray Notes, Part III

X-Ray Notes, Part III oll 6 X-y oe 3: Pe X-Ry oe, P III oe Deeo Coe oupu o x-y ye h look lke h: We efe ue of que lhly ffee efo h ue y ovk: Co: C ΔS S Sl o oe Ro: SR S Co o oe Ro: CR ΔS C SR Pevouly, we ee he SR fo ye hv pxel

More information

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

Content. A Strange World. Clustering. Introduction. Unsupervised Learning Networks. What is Unsupervised Learning? Unsupervised Learning Networks

Content. A Strange World. Clustering. Introduction. Unsupervised Learning Networks. What is Unsupervised Learning? Unsupervised Learning Networks Usupervsed Learg Newors Cluserg Coe Iroduco Ipora Usupervsed Learg NNs Hag Newors Kohoe s Self-Orgazg Feaure Maps Grossberg s AR Newors Couerpropagao Newors Adapve BAN Neocogro Cocluso Usupervsed Learg

More information

Reference: Communication systems-simon Haykin (2001)

Reference: Communication systems-simon Haykin (2001) Reeree: ouao syses-so Hayk haper: I haper, we esgaed he way o odulag a susodal arrer wae usg AM ehque. There s aoher way o odulag a, susodal arrer wae, aely, agle odulao whh he agle o he arrer wae s ared

More information

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state)

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state) Pro. O. B. Wrgh, Auum Quaum Mechacs II Lecure Tme-depede perurbao heory Tme-depede perurbao heory (degeerae or o-degeerae sarg sae) Cosder a sgle parcle whch, s uperurbed codo wh Hamloa H, ca exs a superposo

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

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

Delay-Dependent Robust Asymptotically Stable for Linear Time Variant Systems

Delay-Dependent Robust Asymptotically Stable for Linear Time Variant Systems Delay-Depede Robus Asypocally Sable for Lear e Vara Syses D. Behard, Y. Ordoha, S. Sedagha ABSRAC I hs paper, he proble of delay depede robus asypocally sable for ucera lear e-vara syse wh ulple delays

More information

The Linear Regression Of Weighted Segments

The Linear Regression Of Weighted Segments The Lear Regresso Of Weghed Segmes George Dael Maeescu Absrac. We proposed a regresso model where he depede varable s made o up of pos bu segmes. Ths suao correspods o he markes hroughou he da are observed

More information

EE 6885 Statistical Pattern Recognition

EE 6885 Statistical Pattern Recognition EE 6885 Sascal Paer Recogo Fall 005 Prof. Shh-Fu Chag hp://.ee.columba.edu/~sfchag Lecure 8 (/8/05 8- Readg Feaure Dmeso Reduco PCA, ICA, LDA, Chaper 3.8, 0.3 ICA Tuoral: Fal Exam Aapo Hyväre ad Erkk Oja,

More information

Analysis Of Clustering Algorithms for MR Image Segmentation Using IQI

Analysis Of Clustering Algorithms for MR Image Segmentation Using IQI Avalable ole a www.seedre.o Proeda Teholog 6 (0 ) 387 396 d Ieraoal Coferee o Couao, Copug & Seur [ICCCS-0] Aalss Of Cluserg Algorhs for MR Iage Segeao Usg IQI S. Pael, K.S.Paa Depare of Copuer See ad

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

An AGV-Routing Algorithm in the Mesh Topology with Random Partial Permutation

An AGV-Routing Algorithm in the Mesh Topology with Random Partial Permutation A AGV-Rou Alorhm he Mesh Topoloy wh Radom aral ermuao Ze Jaya, Hsu We-J ad Vee Voo Yee ere for Advaed Iformao Sysems, Shool of ompuer eer Naya Teholoal Uversy, Sapore 69798 {p8589, hsu, ASVYV}@uedus Absra

More information

Outline. Computer Networks: Theory, Modeling, and Analysis. Delay Models. Queuing Theory Framework. Delay Models. Little s Theorem

Outline. Computer Networks: Theory, Modeling, and Analysis. Delay Models. Queuing Theory Framework. Delay Models. Little s Theorem Oule Couer Newors: Theory, Modelg, ad Aalyss Guevara Noubr COM35, lecure 3 Delay Models Lle s Theore The M/M/ queug syse The M/G/ queug syse F, COM35 Couer Newors Lecure 3, F, COM35 Couer Newors Lecure

More information

Some Different Perspectives on Linear Least Squares

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

More information

Fault Tolerant Computing. Fault Tolerant Computing CS 530 Reliability Analysis

Fault Tolerant Computing. Fault Tolerant Computing CS 530 Reliability Analysis Probably /4/6 CS 5 elably Aaly Yahwa K. Malaya Colorado Sae very Ocober 4, 6 elably Aaly: Oule elably eaure: elably, avalably, Tra. elably, T M MTTF ad (, MTBF Bac Cae Sgle u wh perae falure, falure rae

More information

A Weighted Sample s Fuzzy Clustering Algorithm With Generalized Entropy

A Weighted Sample s Fuzzy Clustering Algorithm With Generalized Entropy A Weghted Saple s Fuzzy Clusterg Algorth Wth Geeralzed Etropy Ka L Hebe uversty Shool of atheats ad oputer Baodg, Cha Eal: Lka {at} hbu.edu. Lua Cu Hebe uversty Lbrary Baodg, Cha Abstrat Cobed wth weght

More information

CS344: Introduction to Artificial Intelligence

CS344: Introduction to Artificial Intelligence C344: Iroduco o Arfcal Iellgece Puhpa Bhaacharyya CE Dep. IIT Bombay Lecure 3 3 32 33: Forward ad bacward; Baum elch 9 h ad 2 March ad 2 d Aprl 203 Lecure 27 28 29 were o EM; dae 2 h March o 8 h March

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

Posterior analysis of the compound truncated Weibull under different loss functions for censored data.

Posterior analysis of the compound truncated Weibull under different loss functions for censored data. INRNAIONA JOURNA OF MAHMAIC AND COMUR IN IMUAION Vou 6 oso yss of h oou u Wu u ff oss fuos fo so. Khw BOUDJRDA Ass CHADI Ho FAG. As I hs h Bys yss of gh u Wu suo s os u y II so. Bys sos osog ss hv v usg

More information

Effect of Co-channel Interference. : instantaneous signal power of the desired base station

Effect of Co-channel Interference. : instantaneous signal power of the desired base station Wreless Couo ehologes C559 dved ops Couos geerg Leure 7 Ferury 3 sruor: Dr. ry B. Mdy y Srdhr Muuswy srdhr@wl.rugers.edu Mulple Re or Rylegh erferers ffe of Co-hel erferee roellulr evroes e reeved sgl

More information

Outline. Queuing Theory Framework. Delay Models. Fundamentals of Computer Networking: Introduction to Queuing Theory. Delay Models.

Outline. Queuing Theory Framework. Delay Models. Fundamentals of Computer Networking: Introduction to Queuing Theory. Delay Models. Oule Fudaeals of Couer Neworg: Iroduco o ueug Theory eadg: Texboo chaer 3. Guevara Noubr CSG5, lecure 3 Delay Models Lle s Theore The M/M/ queug syse The M/G/ queug syse F3, CSG5 Fudaeals of Couer Neworg

More information

Abstract. 1. Introduction

Abstract. 1. Introduction Joura of Mathematca Sceces: Advaces ad Appcatos Voume 4 umber 2 2 Pages 33-34 COVERGECE OF HE PROJECO YPE SHKAWA ERAO PROCESS WH ERRORS FOR A FE FAMY OF OSEF -ASYMPOCAY QUAS-OEXPASVE MAPPGS HUA QU ad S-SHEG

More information

Parameters Estimation in a General Failure Rate Semi-Markov Reliability Model

Parameters Estimation in a General Failure Rate Semi-Markov Reliability Model Joura of Saca Theory ad Appcao Vo. No. (Sepember ) - Parameer Emao a Geera Faure Rae Sem-Marov Reaby Mode M. Fahzadeh ad K. Khorhda Deparme of Sac Facuy of Mahemaca Scece Va-e-Ar Uvery of Rafaja Rafaja

More information

Ruin Probability-Based Initial Capital of the Discrete-Time Surplus Process

Ruin Probability-Based Initial Capital of the Discrete-Time Surplus Process Ru Probablty-Based Ital Captal of the Dsrete-Tme Surplus Proess by Parote Sattayatham, Kat Sagaroo, ad Wathar Klogdee AbSTRACT Ths paper studes a surae model uder the regulato that the surae ompay has

More information

A BAYESIAN INFERENCE OF MULTIPLE STRUCTURAL BREAKS IN MEAN AND ERROR VARIANCE IN PANEL AR (1) MODEL

A BAYESIAN INFERENCE OF MULTIPLE STRUCTURAL BREAKS IN MEAN AND ERROR VARIANCE IN PANEL AR (1) MODEL SISICS IN RNSIION ew seres Marh 8 7 SISICS IN RNSIION ew seres Marh 8 Vo. 9 No. pp. 7 3 DOI.37/saras-8- YESIN INFERENCE OF MULIPLE SRUCURL REKS IN MEN ND ERROR VRINCE IN PNEL R ) MODEL Varu gwa Jera Kumar

More information

c- : r - C ' ',. A a \ V

c- : r - C ' ',. A a \ V HS PAGE DECLASSFED AW EO 2958 c C \ V A A a HS PAGE DECLASSFED AW EO 2958 HS PAGE DECLASSFED AW EO 2958 = N! [! D!! * J!! [ c 9 c 6 j C v C! ( «! Y y Y ^ L! J ( ) J! J ~ n + ~ L a Y C + J " J 7 = [ " S!

More information

Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model

Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model . Projec Iroduco Fudameals of Speech Recogo Suggesed Projec The Hdde Markov Model For hs projec, s proposed ha you desg ad mpleme a hdde Markov model (HMM) ha opmally maches he behavor of a se of rag sequeces

More information

Density estimation. Density estimations. CS 2750 Machine Learning. Lecture 5. Milos Hauskrecht 5329 Sennott Square

Density estimation. Density estimations. CS 2750 Machine Learning. Lecture 5. Milos Hauskrecht 5329 Sennott Square Lecure 5 esy esmao Mlos Hauskrec mlos@cs..edu 539 Seo Square esy esmaos ocs: esy esmao: Mamum lkelood ML Bayesa arameer esmaes M Beroull dsrbuo. Bomal dsrbuo Mulomal dsrbuo Normal dsrbuo Eoeal famly Noaramerc

More information

Application of GA Based Fuzzy Neural Networks for Measuring Fouling in Condenser

Application of GA Based Fuzzy Neural Networks for Measuring Fouling in Condenser pplao of G Based Fuzzy eural eors for Measur Foul Codeser Fa Shao-she Chasha Uversy of See ad Teholoy Chasha 40077 Cha fss508@63.om Wa Yao-a Hua Uversy Chasha 4008 Cha yaoa@63.om bsra - ovel approah for

More information

Reliability and Sensitivity Analysis of a System with Warm Standbys and a Repairable Service Station

Reliability and Sensitivity Analysis of a System with Warm Standbys and a Repairable Service Station Ieraoa Joura of Operaos Research Vo. 1, No. 1, 61 7 (4) Reaby ad Sesvy Aayss of a Sysem wh Warm Sadbys ad a Reparabe Servce Sao Kuo-Hsug Wag, u-ju a, ad Jyh-B Ke Deparme of Apped Mahemacs, Naoa Chug-Hsg

More information

Efficient Estimators for Population Variance using Auxiliary Information

Efficient Estimators for Population Variance using Auxiliary Information Global Joural of Mahemacal cece: Theor ad Praccal. IN 97-3 Volume 3, Number (), pp. 39-37 Ieraoal Reearch Publcao Houe hp://www.rphoue.com Effce Emaor for Populao Varace ug Aular Iformao ubhah Kumar Yadav

More information

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005 Seto 2:00 ~ 2:50 pm Thursday Marylad 202 Sep. 29, 2005. Homework assgmets set ad 2 revews: Set : P. A box otas 3 marbles, red, gree, ad blue. Cosder a expermet that ossts of takg marble from the box, the

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