Optimum Demodulation. Lecture Notes 9: Intersymbol Interference
|
|
- Ferdinand Cameron
- 5 years ago
- Views:
Transcription
1 d d Lcur os 9: Irsybol Irrc I his lcur w xai opiu dodulaio wh h rasid sigal is ilrd by h chal ad hr is addiiv whi Gaussia ois. h opiu dodulaor chooss h possibl rasid vcor ha would rsul i h rcivd vcor (i h absc o ois) o b as clos as possibl (i Euclida disac) o wha was rcivd. his w show ca b ipld by a ilr achd o h rcivd sigal or a giv daa sybol ollowd by a oliar procssig via h Virbi algorih. h ilr is sapld a h daa ra. W also aalyz h prorac o such a sys. h aalysis is vry siilar o ha o covoluioal cods. Bcaus h rcivd sigal is ilrd ad sapld, h oupu o h ilr cosiss o wo copos. O du o h rasid sigal ad o du o h ois. h oupu du o ois is, howvr, o whi. Howvr, i h x scio w show ha h oupu o h achd ilr ca b whid. Wih a whid achd ilr h opiu rcivr (Virbi algorih) bcos clar. Fially, i h las scio w show how o dsig a sys o liia irsybol irrc. Opiu Dodulaio Cosidr rasiig daa a ra disorig chal. W would li o id h opiu (iiu squc rror probabiliy) rcivr. Assu h odulaor is a ilr acig o a iii squc o ipulss (a ra wih ipuls rspos. h chal is characrizd by a ipuls rspos o g ad h rcivr is a ilr sapld a ra wih ipuls rspos h. Daa Ra odulaor s h rasid sigal is o h or s u hrough a chal wih badwidh W or hrough a g Chal z u r IX- IX- whr u is h daa sybol rasid durig h -h sigalig irval assud o b i h alphab A ad is h wavor usd or rasissio. W assu a rasissio o daa sybols (hi o as big vry larg). h oupu o h chal ilr is h whr z h g g τ s τ dτ τ u g u h g τ u τ τ dτ τ dτ τ dτ h rcivd sigal cosis o wo rs. O du o sigal ad o du o ois. r su u h whr Sic whr Λ s u u h is whi Gaussia ois h opiu rcivr copus or ach daa squc v v r s v r r s v v v y s v v h r h y sv r h d d v v x d v v v v h h h d h d IX-3 IX-4
2 d s x h h d Sic his is y did arlir h rcivd sigal should b ilrd ad sapld as show blow bor doig so procssig. hus h opiu dcisio rul is Chos v i Λ v ax u Sic h dcisio saisic dpds o h rcivd sigal oly hrough y i is clar ha y is a suici saisic o ipl opial rcivr. Cosidr a ilr h r oupu would b h u Λ. h i h rcivd squc is passd hrough his ilr h y s r h r r h d s d Daa Ra s g z r hr y odulaor Chal Dodulaor y h sapld oupu would b y r h d IX-5 IX-6 odl y η r h h d u h h d η + + y ow h origial coiuous i dcio probl ca b rplacd wih a discr i probl. η y u x η x x x x x u u u u u 3 u IX-7 IX-8
3 d v y v y v y v y v y Opiu Rcivr o ha η is Gaussia. E E Var η η ηη E h Howvr, η is o a i.i.d. squc. odl d h h h d s h s d h s E s dds h x (o ha v j Λ Λ j v v v y ). Assu x x v L (ii irsybol irrc) x v v v x x v x v x v L v v v j v v j i v v j L v x jx jx j i v v j jx j j jx j IX-9 IX- Virbi Algorih h dcisio rul ca b ipld i a Virbi algorih li srucur. Di h sa a i o b h las L daa sybols. (hs ar h oly sybols ha ac h oupu a i ). L h λ σ σ v Λ v σ hus w ca apply h Virbi algorih. λ y L v v x v σ σ v v y L v x x v L Γ σ b h lgh (opiizaio criria) o h shors (opiu) pah o sa σ a i. L Ω σ b h shors pah o sa σ a i. L ˆΓ b h lgh o h pah o sa σ a i ha gos hrough sa σ a i. h algorih wors as ollows., i idx, ˆΩ ˆΩ Γ ˆΓ, σ σ σ Γ σ σ σ v y L ˆΩ σ σ Γσ axσ ˆΓ σ σ Sorag: AL Γ Iiializaio Φ L A (Φ is h py s). x v σ λ σ σ σ argaxσ ˆΓ σ or ach σ σ. ˆΩ Rcursio σ σ σ σ A L ˆΩσ σ σ IX- IX-
4 x, x y y y y x x y y Exapl: L x x, v Λ v λ σ σ y v x v Exapl λ σ σ v y x v v vx v y x x v + + Cosidr a chal wih x lgh 5 ( ). y y 8 x. Cosidr h ollowig rcivd squc o y y x x Assu v. h h rllis is show blow. x x - - x x IX-3 IX-4 rllis rllis + y x y x 4 6 x - y - IX-5 IX-6
5 6 6 y x x y x x x y 4 x rllis rllis 6 x x x x y IX-7 IX y x x y x rllis 6 3 rllis 6 y x 8 y x x 6 IX-8 IX-
6 y x y rllis 6 x x 8 rllis 6 8 x x y x x 8 x x y 8 IX- IX-3 rllis y x rllis v h doubl lis rprs h pah chos by h Virbi dcodr. hus h Virbi dcodr would oupu h squc. y x x IX- IX-4
7 , x y v v v v Exapl: L, x, x, v Λ v λ σ σ v y x v λ σ σ v x v v v x v v x IX-5 IX-6 Error Probabiliy v v v v ric y y x x x x x y x x x x y x x x y x x x y y x x x x x y x x x x ow cosidr h prorac o h abov axiu lilihood squc dcor (LSD). W will valua h uio uppr boud o h rror probabiliy. o do his w d o dri h pairwis rror probabiliy bw wo squcs. his is h probabiliy ha squc v is dodulad giv squc u is rasid or a sys wih oly wo possibl rasid squcs v). L P (u vdo h codiioal rror probabiliy giv u rasid. h P u v u P Q Λ v s v s v s u u s u 4 As cd h pairwis rror probabiliy dpds oly o h squar Euclida disac bw h sigals s u ad s v. s v s u s v s u d Λ u IX-7 IX-8
8 L ε v u s v s u v u v u v 4 4 v u v u v u u h v u ε x 4 v u v u v u ε ε x d h h x h h ε ε x d d P u v 4 4 P ε x j ε x L j ε x ε ε ε ε L jx j jx j ε x ε hus h icral Euclida disac bw wo pahs or a giv i idx is dpds o h pas L rrors. h rror sa is did o b h las L rrors ε ε h all zro rror sa corrspods o h pas L sybols big corrcly dodulad. L A rror v is did o b a rror squc ha divrgs oc ro h all zro sa ad h rrgs lar. Sic a cssary codiio or a rror o a paricular yp (irs v rror or sybol rror) is ha a rror v occurs ha causs h dodulaor/dcodr o ollow a pah ha divrgs ad h a so lar i rrgs w ca calcula h rror probabiliy or a paricular od by couig h ubr o pahs (ad hir disac) ha divrg ad rrg. W ca us h sa diagra o dri h ubr o rror squcs wih a paricular disac.. IX-9 IX-3 L ε P E P b ε wh Haig wigh o (ubr o ozro rs) Firs v rror probabiliy P a i dcodr is o a corrc sa or h irs i Bi rror probabiliy P bi rror occurs or sybol h uio boud o h probabiliy o rror a i is P E u ε v ε P u v u u v whr h su is ovr all squcs ha divrg ro h all zro sa ad h rrg lar. Each o h u squcs ar qually lily. I ach posiio whr ε copos o h squcs u ad v ar drid. I ε h v ad u. Siilarly i ε h v ad u. h copos whr ε hr ar wo choics or u ad v (u v or u v ). Sic hr ar w H placs v P u P u v P u h whr ε hr ar wh P E suchsqucsuadv. Hc ε ε h bi rror probabiliy is boudd by For L P w P w h w H ε P b P wh w w w H ε wh P P ε x L ε x ε ε x εε x W calcula hs uio bouds by uraig h squcs ha divrg ro h all zro rror sa ad rrg (rror vs) ha corrspod o a giv Euclida disac bw wo daa squcs ad has a giv ubr o ozro rs (or is a giv lgh). o do his w draw a sa diagra (siilar o ha or covoluioal cods) ad labl ach pah wih IX-3 IX-3
9 Error Sa Diagra L b + D x x D x l l whr x is h icral Euclida disac squard (dividd by 4) i goig ro o sa o aohr ad l is i h rror pah is ozro ad is zro i h rror is zro. (his rduda us o l will b laid wh w dri h bi rror probabiliy). D x D x Dx x x a d D x c - D x x IX-33 IX-34 rasr Fucio h rasr ucio is calculad by solvig h ollowig quaios or d d c b b Dx xb c Dx Dx xc Dx x c Dxa x b Dxa Addig h las wo quaios ad solvig or b cad subsiuig h rsul io h irs quaio yilds d a D D x D x x D x x Dx x Dx x Dx a. pahs wih wo rrors ad Euclida disac squard o 4x 4x ad so o. P E P b D D x D D x x x x Dx x x D x x x Dx x D For larg SR his is h sa as o ISI! Jus as wih covoluioal cods his Uio-Bhaacharyya boud ca b iprovd by usig h xac rror probabiliy or h irs w rs ad h uppr boudig h rror probabiliy or highr ordr rs wih h Bhaacharyya boud. hus hr ar wo pahs wih rror ad Euclida disac squard o 4x. hr ar wo IX-35 IX-36
10 Ergy oic ha h rgy o h sigal a h oupu o h chal is E Ex s d h uio boud ca b ighly boudd by P b J w j 5 j Q Uio Boud E b j 5 D j 5 w D D x E x E x u h u h l E x u u l h d l u l h l h l d whr E x dos caio wih rspc o h daa bi. Bcaus h daa ar assud idpd, idically disribud wih E x u u l i ladis ohrwis h rgy o h sigal is E u h d IX-37 IX-38 Uio Boud Siulaio Uio Bhaacharrya Boud h x x d P b AWG Hard Dcisio Prorac 8 h rgy pr bi is E be x E b / (db) Figur 6: Prorac o Opial Rcivr (x x ) IX-39 IX-4
11 apl Cod x:=.; x:=.; wih(lialg); a:=**dˆ(x-*x); b:=**dˆ(x+*x); c:=**dˆx; :=arix(3,3,[[-, -, ],[-a, -b, ],[-b, -a, ]]); d:=[, **Dˆx, **Dˆx]; xx:=lisolv(,d); xx:=xx[3]; xx3:=di(xx, ); xx4:=val(xx3, =); xx5:=val(xx4, =.5); xx6:=sipliy(xx5); xx7:=sris(xx6, D=, 5); P b D w D 85 Bouds (x x 75D 5D 5 5D 4 5 5D3 35D 7 5 5D D D D7 5 j w j D j D 4375D6 D ) 875D4 5D 5 5D D D D D D D5 6465D D D D D D IX-4 IX-4 Sigal Dsig or Filrd Chals Bcaus h coplxiy o h Virbi algorih grows as h A L whr is h alphab siz ad L is h ory o h chal i is dsirabl o dsig a sys wih zro irsybol irrc. So cosidr rasiig daa a ra badwidh W. A wha ra is his possibl wihou craig irsybol irrc? Assu h odulaor is a ilr acig o a iii squc o ipulss (a ra ipuls rspos. h chal is characrizd by a ipuls rspos o g ad h rcivr is a ilr sapld a ra wih ipuls rspos h. A hrough a chal wih wih Daa s() g Ra z r h odulaor Chal Dodulaor y y h rasid sigal is o h or s u IX-43 IX-44
12 τ h oupu o h rcivd ilr is h y u x η I ordr ha hr b o irsybol irrc w rquir ha L x x h τ h h τ h d τ d hus by h saplig hor whr I W h x x φ W x W x W si πw πw si πw πw φ W W W W W si x π π h H H whr h. h x is h covoluio o h ad x X H wih. I h (absolu) badwidh o h chal is W h X has badwidh W. ha is h X W x. hus also For o irsybol irrc w rquir ha x x si π π or. L x h IX-45 IX-46 Puls Shap.5 which iplis ha x() hus X i 6 x 5 Spcru H hus W pulss pr scod ca yild zro irsybol irrc. I is asy o s ha by sigalig asr ha ra W w ca o guara ha hr is o irsybol irrc. X() rqucy x 4 Figur 7: yquis Puls Shap ad Spcru IX-47 IX-48
13 .5 Daa Wavor 3.5 x() i Figur 8: yquis Wavor Figur 9: yquis Ey Diagra IX-49 IX yquis Pulss 3 Probls wih his puls shap ar: I is hard o gra A sligh iig rror rsuls i iii sris dcayig as or irsybol irrc. Soluios Sigal slowr Allow irsybol irrc i a corolld ashio Figur : yquis Ey Diagra IX-5 IX-5
14 W, W π π π Irsybol-Irrc Fr Puls Shaps Cosidr slowr sigalig irs. Cosidr. (his iplis aliasig a h rcivr. Sic W wcadivid h irval W io sgs o lgh L W bh ubr o such sgs. Wh h sigal is sapld hs sgs g ovd o h origi ad caus aliasig. x W W X jπ d X X X W jπ d jπ jπ d d. L h x X q X X q Clarly w ca hav zro irsybol irrc i Exapls () X q jπu d IX-53 IX-54 X q x si π cosαπ 4α oic ha h puls dcays as 3 isad o or h yquis puls. h parar α is calld h rollo acor. H si α α α α () h si α π 4α cos 4α π α X si π α α α α IX-55 IX-56
15 Puls Shap.5 Daa Wavor.5 x() i 8 x 5 Spcru x() 6.5 X() rqucy x i Figur : Raisd Cosi Puls Shap ad Spcru (α 5) Figur : Raisd Cosi Wavor (α 5) IX-57 IX-58 x() 3 Raisd Cosi Ey Diagra i Ral(x()) Iag(x()) i Daa Wavor Daa Wavor i Figur 3: Raisd Cosi Ey Diagra α 5 Figur 4: Raisd Cosi Wavor (α 5) IX-59 IX-6
16 Figur 5: Raisd Cosi Wavor Ey Diagra (α 5) Figur 6: Raisd Cosi Wavor (α 5) IX-6 IX-6 Ral(x()) Iag(x()) Daa Wavor i Daa Wavor i Figur 7: Raisd Cosi Wavor π 4 QPSK (α ) Figur 8: Raisd Cosi Wavor Ey Diagra π 4 QPSK (α ) IX-63 IX-64
17 .5 Daa Wavor Ral(x()) Iag(x()) i Daa Wavor i Figur 9: Raisd Cosi Wavor π 4 QPSK (α ) Figur : Raisd Cosi Cosllaio π 4 QPSK (α 5) IX-65 IX Figur : Raisd Cosi Wavor Ey Diagra π 4 QPSK (α 5) Figur : Raisd Cosi Wavor π 4 QPSK (α 5) IX-67 IX-68
18 Ral(x()) Daa Wavor i Daa Wavor 3 Iag(x()) i Figur 3: Raisd Cosi Wavor π 4 QPSK (α 35) Figur 4: Raisd Cosi Wavor Ey Diagra π 4 QPSK (α 35) IX-69 IX avoidig irsybol irrc has h sa prorac as BPSK. h dirc is ha his odulaio sch rquirs absolu badwidh o W α. Howvr, sic his dos o rsul i a cosa vlop sigal or applicaios rquirig cosa vlop rasissio his odulaio sch is o accpabl Figur 5: Raisd Cosi Wavor π 4 QPSK (α 35) Bcaus w do o hav ay irsybol irrc h prorac o his hod or IX-7 IX-7
19 d Corolld Irsybol Irrc: Parial-Rspos h scod hod is o allow so irsybol irrc. his irsybol irrc is allowd i a corolld ashio. W sill sigal a ra Wbudoorquir zro irsybol irrc. x si x π π his is calld Duobiary rasissio (also calld parial rspos class I). Exapl (): X x jπ W W cos π W W W Exapl (): X x x jπ W W W W his is calld odiid Duobiary rasissio (also calld Parial Rspos Class IV). X j W si π W W W his is usd i agic rcordig (wih axiu lilihood dcodig). For hs syss wih corolld irsybol irrc w sill d a way o dc h daa. O hod is dcisio dbac. h ohr hod is prcodig. IX-73 IX-74 Orogoal Frqucy Divisio uliplxig (OFD) Orhogoal rqucy divisio uliplxig (OFD) is a alraiv hod o liiaig irsybol irrc. b L b do h pac o codd daa. his pac is srial-o-paralll covrd io sras o daa ach o lgh L bp. h squcs ar b whr bbp b b b b b b b b b b b b L b bl L Equivally h daa sras ca b wri as a squc o L colu vcors o lgh copos. b b b h daa vcor b is augd wih zros o gra h daa colu vcor C whr C b b b b whr h ladig ad railig zros ar usd o or a guardbad aroud h sigal as will b dscribd subsquly. h vcor C has lgh d. h vcor C is h ipu o a IFF which producs a squc o i sapls o lgh d. hs i doai sapls corrspod o sapls i i wih a saplig ra o IFF wh C is h ipu. ow or purposs o iigaig irsybol irrc prpd a ubr o hs sapls. c c d ν ν c d cd c d. L c do h oupu o h h lgh o c is d νwhrνrprss h lgh o h chal ory (icludig ay ilrig i h rasir ad rcivr). Sic h sapl ra is s corrspodig o c is s ν d. h daa ra is h d ν codd sybols/sc. For d ν h daa ra is approxialy squc o sapls ar h prix isrio or a pac h is giv by d c c 3 c c hs sapls h rprs h sigal a a sapl ra o d l dl l cl ν c s d h duraio d s sybols pr scod. h. hus L IX-75 IX-76
20 4 I h rqucy doai his sigal is S h dsird rasid sigal is s l l c l sic cos π H whr H is a rqucy hoppig par giv by H hp p h Hr hp dos h ubr o hops pr pac, h dos h duraio o a dwll (hop) irval ad p or, is giv by φ l l φl h ad zro lswhr. h ioraio barig phas, pr pac is dod by sp. h dsird RF sigal is obaid by ixig a basbad sigal up o a carrir rqucy via s b s Rs b jπ c Rcosjπ c h cssary basbad rasid sigal is s b l φ l s b sp p l I s b s si jπ c jπ l jbl I ordr or h sigal o hav orhogoal copos i is cssary ha ay pair o rqucis usd ad l saisy l or so igr. W will assu l l sybol irval. I h sigal s b is sapld a spacigs s s s. cosidr h sigal rasid durig a sigl h h sapls ar φ l sp π l bl whr l is h l-h carrir ad b l sybol irval which as valus π π ps s is h daa sybol or h l h carrir durig h -h 3. h ubr o OFD sybols s b l l b l p b l p s jπ l jπ l s IX-77 IX-78 Rcivr A h rcivr h rcivd sigal is r b h opial rcivr dos a coplx corrlaio o dri h daa. sb l b l IFF b jπl Z l s b s b jπ l jπ l d d whr h IFF is h ivrs Fourir rasor. Suppos ha h saplig ra a h rcivr is δ. h Z l L L s L jπ l L L s L L L L b jπ jπl L L jπl L IX-79 IX-8
21 L bl L L b l b b jπ jπ l h calculaio o Z l ca b do via h FF. Z l L jπl L L L L L L s l FF s L jπl whr FF is h as Fourir rasor. h irs valus ro h FF ar h dsird dcisio variabls. L L Cosidr a chal wih irsybol irrc. h i doai daa sigal is c l b l jπl h cyclic prix guard irval orcs c irsybol irrc) is whr h daa via z r c l l l ν h c ν. h rcivd sigal (wih ν is h chal ipuls rspos. h rcivr procsss h rcivd r jπ ν c ν h c ν h u h c u jπ jπ jπ u IX-8 IX-8 whr ν ν ν h h h Hb H jπ jπ jπ u b l l u b ν h l jπ b l jπlu jπ l u jπu Dsig Exapl As a possibl dsig xapl cosidr a sys whr h carrirs ar spacd 5Hz apar ad hr ar d4carrirs wih a guard bad o chals o ach sid. I his cas 64. Igorig h prix isrio w obai a sigal as show i Figur 6. h sigal is upsapld by isrig zros bw h sapls o h origial daa sigal ad ilrig. I Figur 7 w show h cas whr h ovrsaplig is by a acor o 8. h rsulig daa sigal is h ilrd (usig a idal bric wall ilr) ad rsuls i h dsir spcru as s i Figur 8. h daa ra possibl ca b calculad as ollows. Firs, h daa is codd. ypically h cod ra, r,is o h ordr o /4-/. Assu QPSK is usd o ach o h d carrirs ad ach sybol has duraio scods. h daa ra is h R d r ν h badwidh ha is usd dpds o h ilrig do. I hory h badwidh could b as sall as Hz. IX-83 IX-84
22 Spcru Spcru o Ovrsapld Sigal.5 i doai sigal (ral ad iagiary) *log( S() ).5 Spcru o Sigal 3 4 x Phas o Sigal 4 x x 5 Figur 6: Oupu o IFF x 6 Figur 7: Oupu o IFF IX-85 IX-86.5 Badliid vrsio o Ovrsapld Sigal rasir Bloc Diagra x 4 b i FEC b S/P C Zro Pad IFF c Badliid vrsio o Ovrsapld Sigal *log( X() ) x 6 Figur 8: Oupu o IFF Cyclic Prix I DSP S 3C67 c Ovrsapl Filr IQ od D/A Aalog Dvics 9857 (DDS/IQ od) IX-87 IX-88
23 Ey Diagras 5 Sys Parars h DSP gras a pac o codd bis as ollows. A pac o ioraio bis o lgh 48 is usd o as h ipu o a ra /3 cod (covoluioal, urbo or LDPC) producig 644 codd bis. Dpdig o h ulipah o h chal h codword is pucurd o wr bis icrasig h civ ra o h cod. Cosidr h cas o o ulipah iiially. h h codd bis ar pariiod io blocs o lgh 64 which is usd o dri 3 coplx (rqucy doai) sapls. h rqucy doai sapls ar paddd wih zros o ihr sid (6 o ihr sid i his xapl). h rsulig 64 coplx sapls ar usd as ipu o a IFF which producs 64 coplx sapls. For ulipah chals a cyclic prix is addd which allows us o dal wih h irsybol irrc x Figur 9: Ey Diagra x Figur 3: Ey Diagra IX-9 Ey Diagra IX-89 IX-9
Response of LTI Systems to Complex Exponentials
3 Fourir sris coiuous-im Rspos of LI Sysms o Complx Expoials Ouli Cosidr a LI sysm wih h ui impuls rspos Suppos h ipu sigal is a complx xpoial s x s is a complx umbr, xz zis a complx umbr h or h h w will
More informationFourier Series: main points
BIOEN 3 Lcur 6 Fourir rasforms Novmbr 9, Fourir Sris: mai pois Ifii sum of sis, cosis, or boh + a a cos( + b si( All frqucis ar igr mulipls of a fudamal frqucy, o F.S. ca rprs ay priodic fucio ha w ca
More information1973 AP Calculus BC: Section I
97 AP Calculus BC: Scio I 9 Mius No Calculaor No: I his amiaio, l dos h aural logarihm of (ha is, logarihm o h bas ).. If f ( ) =, h f ( ) = ( ). ( ) + d = 7 6. If f( ) = +, h h s of valus for which f
More informationPart B: Transform Methods. Professor E. Ambikairajah UNSW, Australia
Par B: rasform Mhods Profssor E. Ambikairaah UNSW, Ausralia Chapr : Fourir Rprsaio of Sigal. Fourir Sris. Fourir rasform.3 Ivrs Fourir rasform.4 Propris.4. Frqucy Shif.4. im Shif.4.3 Scalig.4.4 Diffriaio
More informationMathematical Preliminaries for Transforms, Subbands, and Wavelets
Mahmaical Prlimiaris for rasforms, Subbads, ad Wavls C.M. Liu Prcpual Sigal Procssig Lab Collg of Compur Scic Naioal Chiao-ug Uivrsiy hp://www.csi.cu.du.w/~cmliu/courss/comprssio/ Offic: EC538 (03)5731877
More informationPoisson Arrival Process
1 Poisso Arrival Procss Arrivals occur i) i a mmorylss mar ii) [ o arrival durig Δ ] = λδ + ( Δ ) P o [ o arrival durig Δ ] = 1 λδ + ( Δ ) P o P j arrivals durig Δ = o Δ for j = 2,3, ( ) o Δ whr lim =
More informationChapter 3 Linear Equations of Higher Order (Page # 144)
Ma Modr Dirial Equaios Lcur wk 4 Jul 4-8 Dr Firozzama Darm o Mahmaics ad Saisics Arizoa Sa Uivrsi This wk s lcur will covr har ad har 4 Scios 4 har Liar Equaios o Highr Ordr Pag # 44 Scio Iroducio: Scod
More informationPoisson Arrival Process
Poisso Arrival Procss Arrivals occur i) i a mmylss mar ii) [ o arrival durig Δ ] = λδ + ( Δ ) P o [ o arrival durig Δ ] = λδ + ( Δ ) P o P j arrivals durig Δ = o Δ f j = 2,3, o Δ whr lim =. Δ Δ C C 2 C
More informationDigital Signal Processing, Fall 2006
Digital Sigal Procssig, Fall 6 Lctur 9: Th Discrt Fourir Trasfor Zhg-Hua Ta Dpartt of Elctroic Systs Aalborg Uivrsity, Dar zt@o.aau.d Digital Sigal Procssig, I, Zhg-Hua Ta, 6 Cours at a glac MM Discrt-ti
More informationECEN620: Network Theory Broadband Circuit Design Fall 2014
ECE60: work Thory Broadbad Circui Dig Fall 04 Lcur 6: PLL Trai Bhavior Sam Palrmo Aalog & Mixd-Sigal Cr Txa A&M Uivriy Aoucm, Agda, & Rfrc HW i du oday by 5PM PLL Trackig Rpo Pha Dcor Modl PLL Hold Rag
More informationELECTROMAGNETIC COMPATIBILITY HANDBOOK 1. Chapter 12: Spectra of Periodic and Aperiodic Signals
ELECTOMAGNETIC COMPATIBILITY HANDBOOK Chapr : Spcra of Priodic ad Apriodic Sigals. Drmi whhr ach of h followig fucios ar priodic. If hy ar priodic, provid hir fudamal frqucy ad priod. a) x 4cos( 5 ) si(
More informationWeb-appendix 1: macro to calculate the range of ( ρ, for which R is positive definite
Wb-basd Supplmary Marials for Sampl siz cosidraios for GEE aalyss of hr-lvl clusr radomizd rials by Sv Trsra, Big Lu, oh S. Prissr, Tho va Achrbrg, ad Gorg F. Borm Wb-appdix : macro o calcula h rag of
More information( A) ( B) ( C) ( D) ( E)
d Smsr Fial Exam Worksh x 5x.( NC)If f ( ) d + 7, h 4 f ( ) d is 9x + x 5 6 ( B) ( C) 0 7 ( E) divrg +. (NC) Th ifii sris ak has h parial sum S ( ) for. k Wha is h sum of h sris a? ( B) 0 ( C) ( E) divrgs
More informationReview Topics from Chapter 3&4. Fourier Series Fourier Transform Linear Time Invariant (LTI) Systems Energy-Type Signals Power-Type Signals
Rviw opics from Chapr 3&4 Fourir Sris Fourir rasform Liar im Ivaria (LI) Sysms Ergy-yp Sigals Powr-yp Sigals Fourir Sris Rprsaio for Priodic Sigals Dfiiio: L h sigal () b a priodic sigal wih priod. ()
More informationEEE 303: Signals and Linear Systems
33: Sigls d Lir Sysms Orhogoliy bw wo sigls L us pproim fucio f () by fucio () ovr irvl : f ( ) = c( ); h rror i pproimio is, () = f() c () h rgy of rror sigl ovr h irvl [, ] is, { }{ } = f () c () d =
More informationNumerical Simulation for the 2-D Heat Equation with Derivative Boundary Conditions
IOSR Joural of Applid Chmisr IOSR-JAC -ISSN: 78-576.Volum 9 Issu 8 Vr. I Aug. 6 PP 4-8 www.iosrjourals.org Numrical Simulaio for h - Ha Equaio wih rivaiv Boudar Codiios Ima. I. Gorial parm of Mahmaics
More informationDepartment of Electronics & Telecommunication Engineering C.V.Raman College of Engineering
Lcur No Lcur-6-9 Ar rdig his lsso, you will lr ou Fourir sris xpsio rigoomric d xpoil Propris o Fourir Sris Rspos o lir sysm Normlizd powr i Fourir xpsio Powr spcrl dsiy Ec o rsr ucio o PSD. FOURIER SERIES
More informationLecture 12: Introduction to nonlinear optics II.
Lcur : Iroduco o olar opcs II r Kužl ropagao of srog opc sgals propr olar ffcs Scod ordr ffcs! Thr-wav mxg has machg codo! Scod harmoc grao! Sum frqucy grao! aramrc grao Thrd ordr ffcs! Four-wav mxg! Opcal
More informationx, x, e are not periodic. Properties of periodic function: 1. For any integer n,
Chpr Fourir Sri, Igrl, d Tror. Fourir Sri A uio i lld priodi i hr i o poiiv ur p uh h p, p i lld priod o R i,, r priodi uio.,, r o priodi. Propri o priodi uio:. For y igr, p. I d g hv priod p, h h g lo
More informationLaguerre wavelet and its programming
Iraioal Joural o Mahaics rds ad chology (IJM) Volu 49 Nubr Spbr 7 agurr l ad is prograig B Sayaaraya Y Pragahi Kuar Asa Abdullah 3 3 Dpar o Mahaics Acharya Nagarjua Uivrsiy Adhra pradsh Idia Dpar o Mahaics
More informationFourier Techniques Chapters 2 & 3, Part I
Fourir chiqus Chaprs & 3, Par I Dr. Yu Q. Shi Dp o Elcrical & Compur Egirig Nw Jrsy Isiu o chology Email: shi@i.du usd or h cours: , 4 h Ediio, Lahi ad Dog, Oord
More informationMixing time with Coupling
Mixig im wih Couplig Jihui Li Mig Zhg Saisics Dparm May 7 Goal Iroducio o boudig h mixig im for MCMC wih couplig ad pah couplig Prsig a simpl xampl o illusra h basic ida Noaio M is a Markov chai o fii
More informationModeling of the CML FD noise-to-jitter conversion as an LPTV process
Modlig of h CML FD ois-o-ir covrsio as a LPV procss Marko Alksic. Rvisio hisory Vrsio Da Comms. //4 Firs vrsio mrgd wo docums. Cyclosaioary Nois ad Applicaio o CML Frqucy Dividr Jir/Phas Nois Aalysis fil
More informationMulti-carrier CDMA (MC-CDMA) with Space time codes
Muli-arrir CDMA (MC-CDMA) wih Spa i ods. Iroduio: Mos of h ods provid high rliabiliy bu hav a low daa ra. H i is lar ha h ods wih high ra ad rliabiliy ar h dsig arg i ids of os rsarhrs. To provid high
More informationSome Applications of the Poisson Process
Applid Maaics, 24, 5, 3-37 Publishd Oli Novbr 24 i SciRs. hp://www.scirp.org/oural/a hp://dx.doi.org/.4236/a.24.59288 So Applicaios of Poisso Procss Kug-Ku s Dpar of Maaics, Ka Uivrsiy, Uio, USA Eail:
More informationNote 6 Frequency Response
No 6 Frqucy Rpo Dparm of Mchaical Egirig, Uivriy Of Sakachwa, 57 Campu Driv, Sakaoo, S S7N 59, Caada Dparm of Mchaical Egirig, Uivriy Of Sakachwa, 57 Campu Driv, Sakaoo, S S7N 59, Caada. alyical Exprio
More informationContinous system: differential equations
/6/008 Coious sysm: diffrial quaios Drmiisic modls drivaivs isad of (+)-( r( compar ( + ) R( + r ( (0) ( R ( 0 ) ( Dcid wha hav a ffc o h sysm Drmi whhr h paramrs ar posiiv or gaiv, i.. giv growh or rducio
More information1a.- Solution: 1a.- (5 points) Plot ONLY three full periods of the square wave MUST include the principal region.
INEL495 SIGNALS AND SYSEMS FINAL EXAM: Ma 9, 8 Pro. Doigo Rodrígz SOLUIONS Probl O: Copl Epoial Forir Sri A priodi ri ar wav l ad a daal priod al o o od. i providd wi a a 5% d a.- 5 poi: Plo r ll priod
More informationPhys463.nb Conductivity. Another equivalent definition of the Fermi velocity is
39 Anohr quival dfiniion of h Fri vlociy is pf vf (6.4) If h rgy is a quadraic funcion of k H k L, hs wo dfiniions ar idical. If is NOT a quadraic funcion of k (which could happ as will b discussd in h
More informationTHE ROYAL STATISTICAL SOCIETY 2016 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA MODULE 1
TH ROAL TATITICAL OCIT 6 AINATION OLTION GRADAT DILOA ODL T oci i providig olio o ai cadida prparig or aiaio i 7. T olio ar idd a larig aid ad old o b a "odl awr". r o olio old alwa b awar a i a ca r ar
More informationECE351: Signals and Systems I. Thinh Nguyen
ECE35: Sigals ad Sysms I Thih Nguy FudamalsofSigalsadSysms x Fudamals of Sigals ad Sysms co. Fudamals of Sigals ad Sysms co. x x] Classificaio of sigals Classificaio of sigals co. x] x x] =xt s =x
More informationWhat Is the Difference between Gamma and Gaussian Distributions?
Applid Mahmaics,,, 85-89 hp://ddoiorg/6/am Publishd Oli Fbruary (hp://wwwscirporg/joural/am) Wha Is h Diffrc bw Gamma ad Gaussia Disribuios? iao-li Hu chool of Elcrical Egirig ad Compur cic, Uivrsiy of
More information8(4 m0) ( θ ) ( ) Solutions for HW 8. Chapter 25. Conceptual Questions
Solutios for HW 8 Captr 5 Cocptual Qustios 5.. θ dcrass. As t crystal is coprssd, t spacig d btw t plas of atos dcrass. For t first ordr diffractio =. T Bragg coditio is = d so as d dcrass, ust icras for
More informationFrom Fourier Series towards Fourier Transform
From Fourir Sris owards Fourir rasform D D d D, d wh lim Dparm of Elcrical ad Compur Eiri D, d wh lim L s Cosidr a fucio G d W ca xprss D i rms of Gw D G Dparm of Elcrical ad Compur Eiri D G G 3 Dparm
More informationLinear Systems Analysis in the Time Domain
Liar Sysms Aalysis i h Tim Domai Firs Ordr Sysms di vl = L, vr = Ri, d di L + Ri = () d R x= i, x& = x+ ( ) L L X() s I() s = = = U() s E() s Ls+ R R L s + R u () = () =, i() = L i () = R R Firs Ordr Sysms
More information(A) 1 (B) 1 + (sin 1) (C) 1 (sin 1) (D) (sin 1) 1 (C) and g be the inverse of f. Then the value of g'(0) is. (C) a. dx (a > 0) is
[STRAIGHT OBJECTIVE TYPE] l Q. Th vlu of h dfii igrl, cos d is + (si ) (si ) (si ) Q. Th vlu of h dfii igrl si d whr [, ] cos cos Q. Vlu of h dfii igrl ( si Q. L f () = d ( ) cos 7 ( ) )d d g b h ivrs
More informationEE Control Systems LECTURE 11
Up: Moy, Ocor 5, 7 EE 434 - Corol Sy LECTUE Copyrigh FL Lwi 999 All righ rrv POLE PLACEMET A STEA-STATE EO Uig fc, o c ov h clo-loop pol o h h y prforc iprov O c lo lc uil copor o oi goo y- rcig y uyig
More informationOverview. Review Elliptic and Parabolic. Review General and Hyperbolic. Review Multidimensional II. Review Multidimensional
Mlil idd variabls March 9 Mlidisioal Parial Dirial Eaios arr aro Mchaical Egirig 5B iar i Egirig Aalsis March 9 Ovrviw Rviw las class haracrisics ad classiicaio o arial dirial aios Probls i or ha wo idd
More informationPart B: Transform Methods. Professor E. Ambikairajah UNSW, Australia
Part B: Trasform Mthods Chaptr 3: Discrt-Tim Fourir Trasform (DTFT) 3. Discrt Tim Fourir Trasform (DTFT) 3. Proprtis of DTFT 3.3 Discrt Fourir Trasform (DFT) 3.4 Paddig with Zros ad frqucy Rsolutio 3.5
More informationFinal Exam : Solutions
Comp : Algorihm and Daa Srucur Final Exam : Soluion. Rcuriv Algorihm. (a) To bgin ind h mdian o {x, x,... x n }. Sinc vry numbr xcp on in h inrval [0, n] appar xacly onc in h li, w hav ha h mdian mu b
More informationLECTURE 13 Filling the bands. Occupancy of Available Energy Levels
LUR 3 illig th bads Occupacy o Availabl rgy Lvls W hav dtrmid ad a dsity o stats. W also d a way o dtrmiig i a stat is illd or ot at a giv tmpratur. h distributio o th rgis o a larg umbr o particls ad
More informationDiscrete Fourier Transform (DFT)
Discrt Fourir Trasorm DFT Major: All Egirig Majors Authors: Duc guy http://umricalmthods.g.us.du umrical Mthods or STEM udrgraduats 8/3/29 http://umricalmthods.g.us.du Discrt Fourir Trasorm Rcalld th xpotial
More informationDTFT Properties. Example - Determine the DTFT Y ( e ) of n. Let. We can therefore write. From Table 3.1, the DTFT of x[n] is given by 1
DTFT Proprtis Exampl - Dtrmi th DTFT Y of y α µ, α < Lt x α µ, α < W ca thrfor writ y x x From Tabl 3., th DTFT of x is giv by ω X ω α ω Copyright, S. K. Mitra Copyright, S. K. Mitra DTFT Proprtis DTFT
More informationIn this section we will study periodic signals in terms of their frequency f t is said to be periodic if (4.1)
Fourier Series Iroducio I his secio we will sudy periodic sigals i ers o heir requecy is said o be periodic i coe Reid ha a sigal ( ) ( ) ( ) () or every, where is a uber Fro his deiiio i ollows ha ( )
More informationReview Lecture 5. The source-free R-C/R-L circuit Step response of an RC/RL circuit. The time constant = RC The final capacitor voltage v( )
Rviw Lcur 5 Firs-ordr circui Th sourc-fr R-C/R-L circui Sp rspons of an RC/RL circui v( ) v( ) [ v( 0) v( )] 0 Th i consan = RC Th final capacior volag v() Th iniial capacior volag v( 0 ) Volag/currn-division
More informationFrequency Measurement in Noise
Frqucy Masurmt i ois Porat Sctio 6.5 /4 Frqucy Mas. i ois Problm Wat to o look at th ct o ois o usig th DFT to masur th rqucy o a siusoid. Cosidr sigl complx siusoid cas: j y +, ssum Complx Whit ois Gaussia,
More informationCSE 245: Computer Aided Circuit Simulation and Verification
CSE 45: Compur Aidd Circui Simulaion and Vrificaion Fall 4, Sp 8 Lcur : Dynamic Linar Sysm Oulin Tim Domain Analysis Sa Equaions RLC Nwork Analysis by Taylor Expansion Impuls Rspons in im domain Frquncy
More informationChapter Taylor Theorem Revisited
Captr 0.07 Taylor Torm Rvisitd Atr radig tis captr, you sould b abl to. udrstad t basics o Taylor s torm,. writ trascdtal ad trigoomtric uctios as Taylor s polyomial,. us Taylor s torm to id t valus o
More informationIdeal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory
Liear Time-Ivaria Sysems (LTI Sysems) Oulie Basic Sysem Properies Memoryless ad sysems wih memory (saic or dyamic) Causal ad o-causal sysems (Causaliy) Liear ad o-liear sysems (Lieariy) Sable ad o-sable
More information2 Dirac delta function, modeling of impulse processes. 3 Sine integral function. Exponential integral function
Chapr VII Spcial Fucios Ocobr 7, 7 479 CHAPTER VII SPECIAL FUNCTIONS Cos: Havisid sp fucio, filr fucio Dirac dla fucio, modlig of impuls procsss 3 Si igral fucio 4 Error fucio 5 Gamma fucio E Epoial igral
More informationAnalysis of Non-Sinusoidal Waveforms Part 2 Laplace Transform
Aalyi o No-Siuoidal Wavorm Par Laplac raorm I h arlir cio, w lar ha h Fourir Sri may b wri i complx orm a ( ) C jω whr h Fourir coici C i giv by o o jωo C ( ) d o I h ymmrical orm, h Fourir ri i wri wih
More information) and furthermore all X. The definition of the term stationary requires that the distribution fulfills the condition:
Assigm Thomas Aam, Spha Brumm, Haik Lor May 6 h, 3 8 h smsr, 357, 7544, 757 oblm For R b X a raom variabl havig ormal isribuio wih ma µ a variac σ (his is wri as ~ (,) X. by: R a. Is X ) a urhrmor all
More informationPractice papers A and B, produced by Edexcel in 2009, with mark schemes. Practice Paper A. 5 cosh x 2 sinh x = 11,
Prai paprs A ad B, produd by Edl i 9, wih mark shms Prai Papr A. Fid h valus of for whih 5 osh sih =, givig your aswrs as aural logarihms. (Toal 6 marks) k. A = k, whr k is a ral osa. 9 (a) Fid valus of
More informationFOURIER ANALYSIS Signals and System Analysis
FOURIER ANALYSIS Isc Nwo Whi ligh cosiss of sv compos J Bpis Josph Fourir Bor: Mrch 768 i Auxrr, Bourgog, Frc Did: 6 My 83 i Pris, Frc Fourir Sris A priodic sigl of priod T sisfis ft f for ll f f for ll
More informationMAT3700. Tutorial Letter 201/2/2016. Mathematics III (Engineering) Semester 2. Department of Mathematical sciences MAT3700/201/2/2016
MAT3700/0//06 Tuorial Lr 0//06 Mahmaics III (Egirig) MAT3700 Smsr Dparm of Mahmaical scics This uorial lr coais soluios ad aswrs o assigms. BARCODE CONTENTS Pag SOLUTIONS ASSIGNMENT... 3 SOLUTIONS ASSIGNMENT...
More informationData Structures Lecture 3
Rviw: Rdix sor vo Rdix::SorMgr(isr& i, osr& o) 1. Dclr lis L 2. Rd h ifirs i sr i io lis L. Us br fucio TilIsr o pu h ifirs i h lis. 3. Dclr igr p. Vribl p is h chrcr posiio h is usd o slc h buck whr ifir
More informationOptimum Receivers for the AWGN channel
Opiu Receivers for he AWG chael Coes Opiu Receiver... Opiu Deodulaor... Correlaio Deodulaor... Mached filer Deodulaor... 5 Frequecy doai ierpreaio of ached filer... 8 he Opiu Deecor... Miiu Disace Deecio...
More informationWorksheet: Taylor Series, Lagrange Error Bound ilearnmath.net
Taylor s Thorm & Lagrag Error Bouds Actual Error This is th ral amout o rror, ot th rror boud (worst cas scario). It is th dirc btw th actual () ad th polyomial. Stps:. Plug -valu ito () to gt a valu.
More informationEE415/515 Fundamentals of Semiconductor Devices Fall 2012
3 EE4555 Fudmls of Smicoducor vics Fll cur 8: PN ucio iod hr 8 Forwrd & rvrs bis Moriy crrir diffusio Brrir lowrd blcd by iffusio rducd iffusio icrsd mioriy crrir drif rif hcd 3 EE 4555. E. Morris 3 3
More informationUNIT I FOURIER SERIES T
UNIT I FOURIER SERIES PROBLEM : Th urig mom T o h crkh o m gi i giv or ri o vu o h crk g dgr 6 9 5 8 T 5 897 785 599 66 Epd T i ri o i. Souio: L T = i + i + i +, Sic h ir d vu o T r rpd gc o T T i T i
More informationDerivation of a Predictor of Combination #1 and the MSE for a Predictor of a Position in Two Stage Sampling with Response Error.
Drivatio of a Prdictor of Cobiatio # ad th SE for a Prdictor of a Positio i Two Stag Saplig with Rspos Error troductio Ed Stak W driv th prdictor ad its SE of a prdictor for a rado fuctio corrspodig to
More informationNON-LINEAR PARAMETER ESTIMATION USING VOLTERRA SERIES WITH MULTI-TONE EXCITATION
NON-LINER PRMETER ESTIMTION USING VOLTERR SERIES WIT MULTI-TONE ECITTION imsh Char Dparm of Mchaical Egirig Visvsvaraya Rgioal Collg of Egirig Nagpur INDI-00 Naliash Vyas Dparm of Mchaical Egirig Iia Isiu
More informationChapter4 Time Domain Analysis of Control System
Chpr4 im Domi Alyi of Corol Sym Rouh biliy cririo Sdy rror ri rpo of h fir-ordr ym ri rpo of h cod-ordr ym im domi prformc pcificio h rliohip bw h prformc pcificio d ym prmr ri rpo of highr-ordr ym Dfiiio
More informationThe Variance-Covariance Matrix
Th Varanc-Covaranc Marx Our bggs a so-ar has bn ng a lnar uncon o a s o daa by mnmzng h las squars drncs rom h o h daa wh mnsarch. Whn analyzng non-lnar daa you hav o us a program l Malab as many yps o
More informationLaw of large numbers
Law of larg umbrs Saya Mukhrj W rvisit th law of larg umbrs ad study i som dtail two typs of law of larg umbrs ( 0 = lim S ) p ε ε > 0, Wak law of larrg umbrs [ ] S = ω : lim = p, Strog law of larg umbrs
More informationAkpan s Algorithm to Determine State Transition Matrix and Solution to Differential Equations with Mixed Initial and Boundary Conditions
IOSR Joural o Elcrcal ad Elcrocs Egrg IOSR-JEEE -ISSN: 78-676,p-ISSN: 3-333, Volu, Issu 5 Vr. III Sp - Oc 6, PP 9-96 www.osrourals.org kpa s lgorh o Dr Sa Traso Marx ad Soluo o Dral Euaos wh Mxd Ial ad
More informationPaper Introduction. ~ Modelling the Uncertainty in Recovering Articulation from Acoustics ~ Korin Richmond, Simon King, and Paul Taylor.
Paper Iroducio ~ Modellig he Uceraiy i Recoverig Ariculaio fro Acousics ~ Kori Richod, Sio Kig, ad Paul Taylor Tooi Toda Noveber 6, 2003 Proble Addressed i This Paper Modellig he acousic-o-ariculaory appig
More informationInfinite Continued Fraction (CF) representations. of the exponential integral function, Bessel functions and Lommel polynomials
Ifii Coiu Fraio CF rraio of h oial igral fuio l fuio a Lol olyoial Coiu Fraio CF rraio a orhogoal olyoial I hi io w rall h rlaio bw ifi rurry rlaio of olyoial orroig orhogoaliy a aroria ifii oiu fraio
More informationUNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS
Answr Ky Nam: Da: UNIT # EXPONENTIAL AND LOGARITHMIC FUNCTIONS Par I Qusions. Th prssion is quivaln o () () 6 6 6. Th ponnial funcion y 6 could rwrin as y () y y 6 () y y (). Th prssion a is quivaln o
More informationChapter 2 The Poisson Process
Chapr 2 Th oisso rocss 2. Expoial ad oisso disribuios 2... Th Birh Modl I scods, a oal of popl ar bor. Sarig a ay poi i im, wha is h waiig im for h firs birh? I milliscods, a oal of lpho calls arriv a
More informationLectures 9 IIR Systems: First Order System
EE3054 Sigals ad Systms Lcturs 9 IIR Systms: First Ordr Systm Yao Wag Polytchic Uivrsity Som slids icludd ar xtractd from lctur prstatios prpard by McCllla ad Schafr Lics Ifo for SPFirst Slids This work
More informationEGR 544 Communication Theory
EGR 544 Commuicaio heory 7. Represeaio of Digially Modulaed Sigals II Z. Aliyazicioglu Elecrical ad Compuer Egieerig Deparme Cal Poly Pomoa Represeaio of Digial Modulaio wih Memory Liear Digial Modulaio
More informationMotivation. We talk today for a more flexible approach for modeling the conditional probabilities.
Baysia Ntworks Motivatio Th coditioal idpdc assuptio ad by aïv Bays classifirs ay s too rigid spcially for classificatio probls i which th attributs ar sowhat corrlatd. W talk today for a or flibl approach
More informationInstitute of Actuaries of India
Insiu of Acuaris of India ubjc CT3 Probabiliy and Mahmaical aisics Novmbr Examinaions INDICATIVE OLUTION Pag of IAI CT3 Novmbr ol. a sampl man = 35 sampl sandard dviaion = 36.6 b for = uppr bound = 35+*36.6
More informationDiscrete Fourier Transform. Nuno Vasconcelos UCSD
Discrt Fourir Trasform uo Vascoclos UCSD Liar Shift Ivariat (LSI) systms o of th most importat cocpts i liar systms thory is that of a LSI systm Dfiitio: a systm T that maps [ ito y[ is LSI if ad oly if
More informationNAME: SOLUTIONS EEE 203 HW 1
NAME: SOLUIONS EEE W Problm. Cosir sigal os grap is so blo. Sc folloig sigals: -, -, R, r R os rflcio opraio a os sif la opraio b. - - R - Problm. Dscrib folloig sigals i rms of lmar fcios,,r, a comp a.
More informationFrequency Response & Digital Filters
Frquy Rspos & Digital Filtrs S Wogsa Dpt. of Cotrol Systms ad Istrumtatio Egirig, KUTT Today s goals Frquy rspos aalysis of digital filtrs LTI Digital Filtrs Digital filtr rprstatios ad struturs Idal filtrs
More informationON H-TRICHOTOMY IN BANACH SPACES
CODRUTA STOICA IHAIL EGA O H-TRICHOTOY I BAACH SPACES Absrac: I his papr w mphasiz h oio of skw-oluio smiflows cosidrd a gralizaio of smigroups oluio opraors ad skw-produc smiflows which aris i h sabiliy
More informationChapter 11 INTEGRAL EQUATIONS
hapr INTERAL EQUATIONS hapr INTERAL EUATIONS Dcmbr 4, 8 hapr Igral Eqaios. Normd Vcor Spacs. Eclidia vcor spac. Vcor spac o coios cios ( ). Vcor Spac L ( ) 4. achy-byaowsi iqaliy 5. iowsi iqaliy. Liar
More informationIntroduction to Mobile Robotics Mapping with Known Poses
Iroducio o Mobile Roboics Mappig wih Kow Poses Wolfra Burgard Cyrill Sachiss Mare Beewi Kai Arras Why Mappig? Learig aps is oe of he fudaeal probles i obile roboics Maps allow robos o efficiely carry ou
More informationMajor: All Engineering Majors. Authors: Autar Kaw, Luke Snyder
Nolr Rgrsso Mjor: All Egrg Mjors Auhors: Aur Kw, Luk Sydr hp://urclhodsgusfdu Trsforg Nurcl Mhods Educo for STEM Udrgrdus 3/9/5 hp://urclhodsgusfdu Nolr Rgrsso hp://urclhodsgusfdu Nolr Rgrsso So populr
More informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 301 Signals & Systms Prof. Mark Fowlr ot St #21 D-T Signals: Rlation btwn DFT, DTFT, & CTFT 1/16 W can us th DFT to implmnt numrical FT procssing This nabls us to numrically analyz a signal to find
More information15/03/1439. Lectures on Signals & systems Engineering
Lcturs o Sigals & syms Egirig Dsigd ad Prd by Dr. Ayma Elshawy Elsfy Dpt. of Syms & Computr Eg. Al-Azhar Uivrsity Email : aymalshawy@yahoo.com A sigal ca b rprd as a liar combiatio of basic sigals. Th
More informationS.Y. B.Sc. (IT) : Sem. III. Applied Mathematics. Q.1 Attempt the following (any THREE) [15]
S.Y. B.Sc. (IT) : Sm. III Applid Mahmaics Tim : ½ Hrs.] Prlim Qusion Papr Soluion [Marks : 75 Q. Amp h following (an THREE) 3 6 Q.(a) Rduc h mari o normal form and find is rank whr A 3 3 5 3 3 3 6 Ans.:
More informationSolutions Manual 4.1. nonlinear. 4.2 The Fourier Series is: and the fundamental frequency is ω 2π
Soluios Maual. (a) (b) (c) (d) (e) (f) (g) liear oliear liear liear oliear oliear liear. The Fourier Series is: F () 5si( ) ad he fudameal frequecy is ω f ----- H z.3 Sice V rms V ad f 6Hz, he Fourier
More informationChap 2: Reliability and Availability Models
Chap : lably ad valably Modls lably = prob{s s fully fucog [,]} Suppos from [,] m prod, w masur ou of N compos, of whch N : # of compos oprag corrcly a m N f : # of compos whch hav fald a m rlably of h
More informationAdvanced Engineering Mathematics, K.A. Stroud, Dexter J. Booth Engineering Mathematics, H.K. Dass Higher Engineering Mathematics, Dr. B.S.
Rfrc: (i) (ii) (iii) Advcd Egirig Mhmic, K.A. Sroud, Dxr J. Booh Egirig Mhmic, H.K. D Highr Egirig Mhmic, Dr. B.S. Grwl Th mhod of m Thi coi of h followig xm wih h giv coribuio o h ol. () Mid-rm xm : 3%
More informationHow to get rich. One hour math. The Deal! Example. Come on! Solution part 1: Constant income, no loss. by Stefan Trapp
O hour h by Sf Trpp How o g rich Th Dl! offr you: liflog, vry dy Kr for o-i py ow of oly 5 Kr. d irs r of % bu oly o h oy you hv i.. h oy gv you ius h oy you pid bc for h irs No d o py bc yhig ls! s h
More informationLecture 1: Numerical Integration The Trapezoidal and Simpson s Rule
Lcur : Numrical ngraion Th Trapzoidal and Simpson s Rul A problm Th probabiliy of a normally disribud (man µ and sandard dviaion σ ) vn occurring bwn h valus a and b is B A P( a x b) d () π whr a µ b -
More information14th Annual i-pcgrid Workshop. Xinzhou Dong. Professor Dept of Electrical Engineering Tsinghua University
14h Aual i-pcgrid Workshop Xizhou Dog Profssor Dp of Elcrical Egirig Tsighua Uivrsiy Cos 1. Iroducio 2. Graio ad faur of Faul grad Travllig Wavs FTW 3. Travllig wavs basd procio for EHV/UHV lis 4. Faul
More informationH is equal to the surface current J S
Chapr 6 Rflcion and Transmission of Wavs 6.1 Boundary Condiions A h boundary of wo diffrn mdium, lcromagnic fild hav o saisfy physical condiion, which is drmind by Maxwll s quaion. This is h boundary condiion
More informationDFT: Discrete Fourier Transform
: Discrt Fourir Trasform Cogruc (Itgr modulo m) I this sctio, all lttrs stad for itgrs. gcd m, = th gratst commo divisor of ad m Lt d = gcd(,m) All th liar combiatios r s m of ad m ar multils of d. a b
More information15. Numerical Methods
S K Modal' 5. Numrical Mhod. Th quaio + 4 4 i o b olvd uig h Nwo-Rapho mhod. If i ak a h iiial approimaio of h oluio, h h approimaio uig hi mhod will b [EC: GATE-7].(a (a (b 4 Nwo-Rapho iraio chm i f(
More informationOption 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges.
Optio Chaptr Ercis. Covrgs to Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Divrgs 8 Divrgs Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Covrgs to Covrgs to 8 Proof Covrgs to π l 8 l a b Divrgt π Divrgt
More information10.3 Autocorrelation Function of Ergodic RP 10.4 Power Spectral Density of Ergodic RP 10.5 Normal RP (Gaussian RP)
ENGG450 Probabiliy ad Saisics for Egieers Iroducio 3 Probabiliy 4 Probabiliy disribuios 5 Probabiliy Desiies Orgaizaio ad descripio of daa 6 Samplig disribuios 7 Ifereces cocerig a mea 8 Comparig wo reames
More informationCS 688 Pattern Recognition. Linear Models for Classification
//6 S 688 Pr Rcogiio Lir Modls for lssificio Ø Probbilisic griv modls Ø Probbilisic discrimiiv modls Probbilisic Griv Modls Ø W o ur o robbilisic roch o clssificio Ø W ll s ho modls ih lir dcisio boudris
More informationBE.430 Tutorial: Linear Operator Theory and Eigenfunction Expansion
BE.43 Tuorial: Liear Operaor Theory ad Eigefucio Expasio (adaped fro Douglas Lauffeburger) 9//4 Moivaig proble I class, we ecouered parial differeial equaios describig rasie syses wih cheical diffusio.
More informationA 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 informationChapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series
Chatr Ifiit Sris Pag of Sctio F Itgral Tst Chatr : Ifiit Sris By th d of this sctio you will b abl to valuat imror itgrals tst a sris for covrgc by alyig th itgral tst aly th itgral tst to rov th -sris
More informationSphere-packing Bound for Block-codes with Feedback and Finite Memory
ISIT 010, Ausi, Txas, USA, Ju 13-18, 010 Sphr-packig Boud for Block-cods wih Fdback ad Fii Mmor Giacomo Como Massachuss Isiu of Tcholog Laboraor for Iformaio ad Dcisio Ssms Absrac A lowr boud boud is sablishd
More information